null: str,
*,
mu: float | None = None,
- p: float | None = None,
+ p: float | dict | None = None,
sigma: float | None = None,
) -> Hypothesis:
if null not in ("point", "independence", "paired independence"):
@@ -353,7 +353,7 @@ Source code for moderndive.infer.core
*,
order: tuple[object, object] | None = None,
mu: float | None = None,
- p: float | None = None,
+ p: float | dict | None = None,
sigma: float | None = None,
) -> ObservedStatistic:
"""Compute the observed statistic (no resampling)."""
@@ -407,7 +407,7 @@ Source code for moderndive.infer.core
spec: Specification
null: str
mu: float | None = None
- p: float | None = None
+ p: float | dict | None = None
sigma: float | None = None
def generate(
@@ -449,7 +449,7 @@ Source code for moderndive.infer.core
plans: list[np.ndarray] = field(repr=False)
shifted_response: np.ndarray | None = field(default=None, repr=False)
hyp_mu: float | None = None
- hyp_p: float | None = None
+ hyp_p: float | dict | None = None
hyp_sigma: float | None = None
# --- single-variable / two-group statistics ---------------------------
@@ -567,12 +567,20 @@ Source code for moderndive.infer.core
elif type == "draw":
if hypothesis is None or hypothesis.p is None:
raise ValueError("type='draw' requires hypothesize(null='point', p=...)")
- success = spec.success
- nonsuccess = "\x00not_success"
- p0 = hypothesis.p
- for _ in range(reps):
- draws = rng.random(n) < p0
- plans.append(np.where(draws, success, nonsuccess).astype(object))
+ if isinstance(hypothesis.p, dict):
+ # Multi-level draw for chi-square goodness-of-fit: sample each
+ # replicate's categories from the hypothesized proportions.
+ levels = list(hypothesis.p.keys())
+ probs = np.asarray(list(hypothesis.p.values()), dtype=float)
+ for _ in range(reps):
+ plans.append(rng.choice(levels, size=n, p=probs).astype(object))
+ else:
+ success = spec.success
+ nonsuccess = "\x00not_success"
+ p0 = hypothesis.p
+ for _ in range(reps):
+ draws = rng.random(n) < p0
+ plans.append(np.where(draws, success, nonsuccess).astype(object))
else: # bootstrap
if hypothesis is not None and hypothesis.null == "point" and hypothesis.mu is not None:
shifted = _resample.shift_for_point_null(
@@ -770,7 +778,7 @@ Source code for moderndive.infer.core
order: tuple[object, object] | None = None,
null: str | None = None,
mu: float | None = None,
- p: float | None = None,
+ p: float | dict | None = None,
sigma: float | None = None,
) -> ObservedStatistic:
"""Shortcut for ``specify() |> [hypothesize()] |> calculate()``.
diff --git a/doc/_build/html/_modules/moderndive/infer/wrappers.html b/doc/_build/html/_modules/moderndive/infer/wrappers.html
index ed7872f..d4a873f 100644
--- a/doc/_build/html/_modules/moderndive/infer/wrappers.html
+++ b/doc/_build/html/_modules/moderndive/infer/wrappers.html
@@ -386,13 +386,34 @@ Source code for moderndive.infer.wrappers
formula: str | None = None,
response: str | None = None,
explanatory: str | None = None,
+ p: dict | None = None,
) -> pl.DataFrame:
- """Chi-squared test of independence (categorical response ~ categorical explanatory)."""
+ """Tidy chi-squared test.
+
+ With an explanatory variable, this is a **test of independence**. With only a
+ response and a ``p={level: probability, ...}`` mapping, it is a **goodness-of-fit**
+ test against those hypothesized proportions. Returns ``statistic``,
+ ``chisq_df``, ``p_value``.
+ """
from scipy import stats
resp, expl = _resolve(formula, response, explanatory)
if expl is None:
- raise ValueError("chisq_test needs an explanatory variable (test of independence)")
+ if p is None:
+ raise ValueError(
+ "chisq_test needs either an explanatory variable (test of independence) "
+ "or p={level: probability, ...} (goodness-of-fit)."
+ )
+ counts = data.select(resp).drop_nulls()[resp].value_counts()
+ observed = {row[resp]: row["count"] for row in counts.iter_rows(named=True)}
+ total = sum(observed.values())
+ levels = list(p.keys())
+ f_obs = [observed.get(lvl, 0) for lvl in levels]
+ f_exp = [total * p[lvl] for lvl in levels]
+ chi2, pval = stats.chisquare(f_obs, f_exp)
+ return pl.DataFrame(
+ {"statistic": [float(chi2)], "chisq_df": [len(levels) - 1], "p_value": [float(pval)]}
+ )
sub = data.select(resp, expl).drop_nulls()
table = sub.to_pandas().pivot_table(index=resp, columns=expl, aggfunc="size", fill_value=0)
chi2, pval, dof, _ = stats.chi2_contingency(table.to_numpy(), correction=False)
diff --git a/doc/_build/html/_sources/guides/hypothesis-testing.md.txt b/doc/_build/html/_sources/guides/hypothesis-testing.md.txt
index e4c3302..2c01998 100644
--- a/doc/_build/html/_sources/guides/hypothesis-testing.md.txt
+++ b/doc/_build/html/_sources/guides/hypothesis-testing.md.txt
@@ -99,6 +99,31 @@ null_p = (
`"diff in props"`, `"ratio of means"`, `"ratio of props"`, `"odds ratio"`,
`"slope"`, `"correlation"`, `"t"`, `"z"`, `"F"`, `"Chisq"`.
+## Chi-square goodness-of-fit
+
+For a single categorical variable with several levels, test whether the observed
+counts match a set of hypothesized proportions: `hypothesize(null="point", p=...)`
+with `p` a `{level: probability}` mapping, then `generate(type="draw")` to simulate
+from those proportions.
+
+```{code-cell} python
+gss = md.load_gss()
+levels = gss["finrela"].unique().to_list()
+uniform = {level: 1 / len(levels) for level in levels} # "all classes equally likely"
+
+obs_gof = gss.specify(response="finrela").hypothesize(null="point", p=uniform).calculate(stat="Chisq")
+
+null_gof = (
+ gss.specify(response="finrela")
+ .hypothesize(null="point", p=uniform)
+ .generate(reps=1000, type="draw", seed=1)
+ .calculate(stat="Chisq")
+)
+get_p_value(null_gof, obs_stat=obs_gof, direction="greater")
+```
+
+The one-line wrapper is `chisq_test(gss, response="finrela", p=uniform)`.
+
## Custom test statistics
Beyond those strings, `stat=` accepts **any function** that takes the response
diff --git a/doc/_build/html/api.html b/doc/_build/html/api.html
index a884744..590abfd 100644
--- a/doc/_build/html/api.html
+++ b/doc/_build/html/api.html
@@ -303,7 +303,7 @@ Inference grammartuple[object, object] | None)
null (str | None)
mu (float | None)
p (float | None)
sigma (float | None)
Inference grammar
@@ -399,7 +399,7 @@ Inference grammarSpecification)
null (str)
mu (float | None)
p (float | None)
sigma (float | None)
Inference grammarlist[ndarray])
shifted_response (ndarray | None)
hyp_mu (float | None)
hyp_p (float | None)
hyp_sigma (float | None)
Theory-based tests
-moderndive.chisq_test(data, *, formula=None, response=None, explanatory=None)[source]¶
-Chi-squared test of independence (categorical response ~ categorical explanatory).
+moderndive.chisq_test(data, *, formula=None, response=None, explanatory=None, p=None)[source]¶
+Tidy chi-squared test.
+With an explanatory variable, this is a test of independence. With only a
+response and a p={level: probability, ...} mapping, it is a goodness-of-fit
+test against those hypothesized proportions. Returns statistic,
+chisq_df, p_value.
- Return type:
DataFrame
@@ -713,6 +717,7 @@ Theory-based testsstr | None)
response (str | None)
explanatory (str | None)
p (dict | None)
diff --git a/doc/_build/html/guides/hypothesis-testing.html b/doc/_build/html/guides/hypothesis-testing.html
index e1ec046..4aaf49b 100644
--- a/doc/_build/html/guides/hypothesis-testing.html
+++ b/doc/_build/html/guides/hypothesis-testing.html
@@ -369,6 +369,42 @@ Available statistics"diff in props", "ratio of means", "ratio of props", "odds ratio",
"slope", "correlation", "t", "z", "F", "Chisq".
+
+Chi-square goodness-of-fit¶
+For a single categorical variable with several levels, test whether the observed
+counts match a set of hypothesized proportions: hypothesize(null="point", p=...)
+with p a {level: probability} mapping, then generate(type="draw") to simulate
+from those proportions.
+
+
+gss = md.load_gss()
+levels = gss["finrela"].unique().to_list()
+uniform = {level: 1 / len(levels) for level in levels} # "all classes equally likely"
+
+obs_gof = gss.specify(response="finrela").hypothesize(null="point", p=uniform).calculate(stat="Chisq")
+
+null_gof = (
+ gss.specify(response="finrela")
+ .hypothesize(null="point", p=uniform)
+ .generate(reps=1000, type="draw", seed=1)
+ .calculate(stat="Chisq")
+)
+get_p_value(null_gof, obs_stat=obs_gof, direction="greater")
+
+
+
+
+
+shape: (1, 1)p_value f64 0.0
+
+The one-line wrapper is chisq_test(gss, response="finrela", p=uniform).
+
Custom test statistics¶
Beyond those strings, stat= accepts any function that takes the response
@@ -473,6 +509,7 @@
Custom test statisticsShade the p-value
One mean / one proportion (point null)
Available statistics
+Chi-square goodness-of-fit
Custom test statistics
diff --git a/doc/_build/html/searchindex.js b/doc/_build/html/searchindex.js
index 51e8eab..37869dd 100644
--- a/doc/_build/html/searchindex.js
+++ b/doc/_build/html/searchindex.js
@@ -1 +1 @@
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diff --git a/doc/_build/jupyter_execute/datasets.ipynb b/doc/_build/jupyter_execute/datasets.ipynb
index f290675..351ffc1 100644
--- a/doc/_build/jupyter_execute/datasets.ipynb
+++ b/doc/_build/jupyter_execute/datasets.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "5dc6ac84",
+ "id": "1bfcc312",
"metadata": {
"tags": [
"remove-input"
@@ -19,7 +19,7 @@
},
{
"cell_type": "markdown",
- "id": "2f95db86",
+ "id": "8869ad7a",
"metadata": {},
"source": [
"# Datasets\n",
@@ -31,7 +31,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "01a845a8",
+ "id": "8b5fb72e",
"metadata": {},
"outputs": [
{
@@ -82,7 +82,7 @@
},
{
"cell_type": "markdown",
- "id": "264241e4",
+ "id": "88c3d0f7",
"metadata": {},
"source": [
"## By topic\n",
diff --git a/doc/_build/jupyter_execute/getting-started.ipynb b/doc/_build/jupyter_execute/getting-started.ipynb
index 5cecbcc..051ae0e 100644
--- a/doc/_build/jupyter_execute/getting-started.ipynb
+++ b/doc/_build/jupyter_execute/getting-started.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "49ac7be9",
+ "id": "abe0280c",
"metadata": {
"tags": [
"remove-input"
@@ -19,7 +19,7 @@
},
{
"cell_type": "markdown",
- "id": "afd4aee3",
+ "id": "fea27be9",
"metadata": {},
"source": [
"# Getting started\n",
@@ -44,7 +44,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "155e7515",
+ "id": "48ac6430",
"metadata": {},
"outputs": [
{
@@ -88,7 +88,7 @@
},
{
"cell_type": "markdown",
- "id": "fd3539da",
+ "id": "14b26543",
"metadata": {},
"source": [
"List everything that's available with `md.available_datasets()` (58 datasets), and\n",
@@ -110,7 +110,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "eb3ad4a6",
+ "id": "7410aa14",
"metadata": {},
"outputs": [
{
@@ -149,7 +149,7 @@
},
{
"cell_type": "markdown",
- "id": "5fff89f4",
+ "id": "a3d02e79",
"metadata": {},
"source": [
"`count_missing` reports how many `null` values each column has, sorted worst-first\n",
@@ -159,7 +159,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "a81053f7",
+ "id": "c8cd6b75",
"metadata": {},
"outputs": [
{
@@ -208,7 +208,7 @@
},
{
"cell_type": "markdown",
- "id": "03cfbc91",
+ "id": "a8e21ac9",
"metadata": {},
"source": [
"## The inference pipeline\n",
@@ -220,7 +220,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "05842913",
+ "id": "49486859",
"metadata": {},
"outputs": [
{
@@ -274,7 +274,7 @@
},
{
"cell_type": "markdown",
- "id": "472f54be",
+ "id": "2c752788",
"metadata": {},
"source": [
"Each verb has a focused guide: {doc}`guides/sampling`,\n",
@@ -294,14 +294,14 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "2183feca",
+ "id": "8d27b66e",
"metadata": {},
"outputs": [
{
"data": {
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pp6UJEyakPfbYo92fAQAAAADaIvsA8Omnny7CvAjg7rrrrjR//vwWX7Ns2bKi9t7IkSPTeeed16b3KoV/hx56aDrkkENSv3790sKFC9PFF1+cbrrppvSLX/wibbrppkXzYQAAAACotewDwG9/+9tpwYIFbXpN9P+3ePHiNGbMmDa97oorrijut9lmm3TEEUfU/33AgAHpc5/7XHr88ceLWoh/+ctf0lFHHdWmeQMAK6ZPnz6+QgAAeqTsRwFed911i2a8pVvv3i1/5AjpSq8tDeYxderUoilvU6KW37/+9a/i8b777lvxpGO77bYrHrfUtyAAUH0G5AIAoKfKvgbg2Wef3eD/MRDH3LlzW9X/X4R6J554Ypo4cWKqq6sr/jZ69Oh04IEHpn322Sf16tWr/jXRxHjJkiXF397znvdUnO/mm2+err322mL+8+bNcyICAAAAQM1lHwC2R6kG4I033ljcr7zyysUt+gWcNm1a0Y9f9Pd3/PHH14eApRF/hw0b1mSwF30KljczHjt2bAd8GgConhtuuKH4LezO4mLe/vvv39mLAQAAHUYA2EwAuNJKK6UvfvGLaccddyz+P2fOnGKU3xjM4+9//3taf/31i9qApefC0KFDm/yyy59rbjCS6LMwah82NUBJiBqJbe3bsLtatGhRg3soib46e8p+QOsoL2ojLnZFf7Yhwr/oFiMX8XtbquWfw/rJTa3XT0eUGTmvn8WLl8RRaereeqV+/fI8Jcpj/XS17/M/91CydOnS4rwE2lRmdMLxZ56/disoRu6N/gKPOeaYtMkmm9T/fciQIem4444rwr4YUfjqq69OBxxwQNGvYCnQ69u36a+0f//+ywV5lUyZMiVNmjSpxULmpZdeSj1JqZYlgPKiYw0cOLDNA2N1FxFodvcLCdZP1z7GyHn9zJjxTrc/6Y3j/lGjRqUc5bB+uur3CrCiZcayqCDWijEqqkkAWME3vvGNZr+0D37wg0UAOHPmzPTKK6+kddZZpzh4aKlmX/nV5UGDBjU5XTQNXn311Ss+d//99xfziUFFcj2YbCw+bxyYx3dSHqKCvjRRXnSM8j5vcxPNgXOoAZirWq+fjjjGyHn9DBs2PIMaZtYPrRO1eOJEPrb7XGuN0v7a6rnW9KZ2ZcaUTmjhqORq58FoSanp7yqrrNLg/5XMmDGjYn+Ala4Ux62S0ijGcTDZ1DS5igPznvaZaV5c1bZNUInygtZywN61ddT6UWa0jxCka7N+ave9lip/QIjBQG0TtLnMiBraHXwRumPrG3YD77zzTnr++efrRwJuaprG/fpFLcAwe/bsYoCPSqK2YBg+fHgxqAgAAAAA1JoAsJF77703feUrX0mnnHJKk1/a448/Xj9IyJprrlk83mijjeqvUj/66KMVX/fwww8X91tssUV11h4AAAAAtEAA2Mhmm21W3L/xxhvpb3/7W8VmvDH4R/jABz5Q3yQ3qnTutNNOxeN4PvomK/fcc8+lu+++u3i8xx57tLReAAAAAKAq9AHYSDTl3WGHHdJ9992Xzj///GI03u22267oZ+yFF15IV111VTH4RzThPeSQQxq89rDDDite9+qrr6aTTz45HXzwwWnEiBFp4sSJ6corryz6Bthxxx3T5ptvXp21BwAAAAAtEABWEE2AzzrrrKIp7/XXX1/cykWoF02ESwN/lA8OcuKJJ6azzz67qPF35plnNnh+0003TRMmTGhpnQAAAABA1fS4AHDs2LFp/vz59YN3VDJ48OB02mmnpYceeqhothuDd8SouxH8Re29aPrb1MijW221VbrgggvSX//616LmX7zXqFGjilqF73vf+1KfPn1q+OkAAAAAoIcHgI1r5TVn2223LW5tteqqq6Yjjjiiza8DAAAAgGozCAgAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxqoaAE6ePDmdeuqp6bLLLuuQ1wEAAAAAHRwAnnbaaW0O8p599tl2vQ4AAAAA6OJNgOvq6tIdd9xRPO7Tp09nLw4AAAAAZKVve194++23p4MOOqjB35YsWVL/3LBhw1o1n0WLFqX58+cXj0ePHt3exQEAAAAAqhkALl68OM2cObPicxEENvVcU3r37p2OOOKI9i4OAAAAAFDNADBq+G2//fYN/hah3zPPPJNWWWWVtPHGG7dqPoMGDUrjxo1LRx999HLzAwAAAAA6KQDcYYcd0n333dfgbzfffHPaZ599iufiMQAAAACQ0SAg/fr1K2r/DRkypJqzBQAAAAA6ugZgJbvvvnuaMWNGNWcJAAAAAHSVGoAAAAAAQMY1AMvdddddRT+Azz33XJo9e3ZaunRpi6/Zdttt03e/+91aLRIAAAAA9DhVDwAXLlyYPv7xj6c//vGP1Z41AAAAANDZTYBPPvlk4R8AAAAA5FgDMGr//epXvyoejxkzJp1++unpAx/4QFpttdVSnz59Wnx97966JAQAAACALhsAPv3002nWrFmpb9++6Y477kjjxo2r5uwBAAAAgDaqapW7t99+u7jfZptthH8AAAAAkFsAuMoqqxT3gwcPruZsAQAAAICuEABuvPHGacCAAWnixIlp2bJl1Zw1AAAAANDZAeBKK62U9t9///Tqq6+myy+/vJqzBgAAAADaoerD7n7ve98rmgAfe+yx6aabbqr27AEAAACAzhoFeMaMGenNN99Mxx13XPrBD36Q9ttvv7TnnnumnXfeOY0aNapoHtyctdZaq5geAAAAAOiCAeB9992X9tlnn/r/19XVpVtuuaW4tcbee+8tAAQAAACArtwEGAAAAADItAbg1ltvna655pp2v3706NHVXBwAAAAA6PGqGgCuttpq6cMf/nCP/1IBAAAAoKvQBBgAAAAAMiYABAAAAICMVbUJ8OTJk9Nll13W7tdvsMEG6cgjj6zmIgEAAABAj1b1APC0005r9+v33ntvASAAAAAAVJEmwAAAAACQsarWAHzf+96XHn300WanWbp0aZozZ06aOnVqeuCBB9Lvf//79NZbb6Vdd921eEzrLFu2LM2ePbvHfNahQ4emhQsXpsWLF3f24tCFLFmypMfsB7SO8qI2+vTpkwYPHpzlZjhv3rzi2KQ7s366dpmR8/qJ7y2+w+6sd+/eacCAASlHOayfrqSuri4NGjSoKCviGBRKli5dlubPn+8LoU1lRjzfrQPAOIDacsstWz199Pf33e9+N33+859Pl19+efrkJz+ZrrvuumouUrbiYCW+755gwYIFadq0aWn48OFp4MCBnb04dCER/vWU/YDWUV7QVrkGM7mo9fpRZqyYXIOzXFg/1RUn8TNmzEhDhgxJ/fr1q/Lc6c4i/IugB9pSZvSaNy9SwNSjmgCvvPLK6be//W0RHF5//fXp7rvv7uxFAgAAAIBsdHoAWKrN9ulPf7p4/Oc//7mzFwcAAAAAstElAsAwZsyY4v65557r7EUBAAAAgGx0mQDw5Zdfrq8NCAAAAABUR5dI295+++10/vnnF4/XXnvtzl4cAAAAAMhGVUcBfuWVV9Ktt97aptFynn322fT73/++GOU17LffftVcJAAAAADo0aoaAP7rX/+qH8yjPfbdd9+05557VnORAAAAAKBH6xJNgFdaaaU0YcKE9Kc//amzFwUAAAAAslLVGoCbbbZZ+vWvf93q6YcMGZJGjx6dttlmmzR48OBqLgoAAAAAUO0AcK211kqf+tSnfLEAAAAA0EV0iSbAAAAAAEA3qAHY1Ei/999/fzHa7/Tp01O/fv3SyJEji+bCW2yxRfF/AAAAAKCbBYBvvfVWOv3009NFF11UhICVDB8+PB155JHppJNOSquvvnqtFgUAAAAAeqyaNAF+5pln0vjx49MFF1zQZPgX3nnnnWKajTfeOF111VW1WBQAAAAA6NGqXgNw1qxZ6YMf/GB68cUXi/+vs8466YADDkgbbrhhWm211YpA8NVXX02TJk1K119/fXr77bfTzJkz06GHHpquu+66tO+++1Z7kQAAAACgx6p6AHjuueemyZMnpwEDBqSf/vSn6aijjmpy2sWLF6ebbropHX/88em5555Lxx13XJo4cWIaOHBgtRcLAAAAAHqkqjYBrqurS7/61a+Kx9G0t7nwL8QAIB/60IfSXXfdVdQOfOmll9Jtt91WzUUCAAAAgB6tqgFgjPT7+uuvF6P8fupTn2r169ZYY4109NFHF4/vvPPOai4SAAAAAPRoVQ0AX3vtteI+BvWI2n1tscUWWxT30T8gAAAAANAFA8Do9y8sW7asXc2HQ3OjBgMAAAAAnRgAjhkzprj/17/+lebOndum1z7yyCPF/ejRo6u5SAAAAADQo1U1AFxrrbXSpptumubMmZNOP/30Vr8umv1edNFFxeOdd965mosEAAAAAD1aVQPAcPzxxxf3Z599dvr0pz+dXn755Wan/9vf/pZ22mmnNH369DRq1KhiVGAAAAAAoDr6piqL0X+vvfbadN1116Xf/OY36bLLLisCvh122CGNHTs2DRo0qGgePGnSpHTbbbelJ598sv615513Xlp55ZWrvUgAAAAA0GNVPQDs1atXuvLKK9PRRx9dhH9LliwpavnFrSn9+/dPP/7xj9Phhx9e7cUBAAAAgB6t6k2Aw8CBA9Oll16abrzxxrTnnnumPn36NBn8HXbYYenhhx9Oxx13XC0WBQAAAAB6tKrXACy3zz77FLcYFCRCvtdffz3Nnj07DR06NK299tppm222KcJCAAAAAKAbBoDh7bffTm+88UbaZZddlvv7m2++mdZZZ51aLwIAAAAA9Fg1aQJcV1dXNAHebrvt0siRI9NXvvKV5aZ54IEH0pgxY9LGG2+cfvKTn6SlS5fWYlEAAAAAoEfrXYvw7+Mf/3j6xCc+kR588MEWp584cWL64he/mHbfffeiqTAAAAAA0IUDwF/96lfp8ssvLx4PGjSoCAMnTJiw3HSbb755+sIXvpBGjx5d/P/vf/97EQQCAAAAAF04ADz33HOL+9122y1NmjQp/fa3v03777//ctOtueaaRdPfmOZTn/pU8bdLLrmkqBEIAAAAAHTBAPCll14qAr0Y2fcPf/hDWmuttVp8TYwIfPHFFxeBYTQfvvbaa6u5SAAAAADQo1U1AHzxxReL+6222iqtuuqqrX5dr1690pFHHlk8/te//lXNRQIAAACAHq2qAWDU4CsFem0VowWHWbNmVXORAAAAAKBHq2oAWGry++9//zvNnTu3Ta995plnGgSBAAAAAEAXCwA32GCDtP7666eZM2emk046qdWvmzFjRvrZz35WPB4/fnw1FwkAAAAAerSqjwL81a9+tbg///zz00c+8pEW+/S744470nvf+95iAJEYEOSjH/1otRcJAAAAAHqsvtWe4THHHJNuuOGGdNNNN6VrrrmmuI0dOzbttNNOabXVVksjRoxIixYtKgYMufvuu9MLL7xQ/9of/OAHxTQAAAAAQBcNAPv06ZOuuuqqdNRRR6Xf//73xd+mTJlS3JrSv3//dO6556ajjz662osDAAAAAD1a1ZsAh0GDBqXf/e536S9/+Uvaa6+9ilCwqeDvsMMOSw8//HD64he/WItFAQAAAIAereo1AMvtu+++xW3evHnpkUceSa+++mqaPXt2Gjx4cFp77bXTtttuW4SFAAAAAEA3DABLIvCLPgABAAAAgAyaAAMAAAAAXYMAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADLWN/Uw11xzTfrTn/6UPv/5z6f3ve99zU776quvFtNPmjQpzZo1K40YMSJttdVWad99903Dhw+v+usAAAAAoNp6VAC4cOHC9Je//CXNnj07LVq0qNlpH3roofT9738/LVmypP5vb731Vnr22WfTX//61/Stb30rbbDBBlV7HQAAAADUQo8IAKdPn54mTpyYrr322vTGG2+0OP2bb76ZzjzzzCLE22yzzdLHPvaxNHr06PTKK6+kSy65JE2ePLl4/vzzz0+DBw9e4dcBAAAAQK1kHwAeccQRRY2/trjyyiuLGoLrrLNOOvXUU1O/fv2Kv6+66qrptNNOS8cee2wRJEaNvgMPPHCFXwcAAAAAtZL9ICCLFy9u0/TLli1L99xzT/H4wx/+cH2IVzJ06NC03XbbFY9L063I6wAAAACglrKvAXjRRRc1+P/nPve5NG/evCanf/7559PcuXOLx1tvvXXFabbccst0++23F016I2CMsK+9rwMAAACAWsq+BuDKK6/c4NarV69mp58yZUpxv9JKK6WRI0dWnGattdaqr/UX/f6tyOsAAAAAoJayrwHYVrNmzSruhw0b1uQ0Q4YMqX88Z86cFXpdJQsWLChGLK4kwsNQV1dXTNcTlEZsbmnkZnqeqEnbU/YDWkd5URtx8WzAgAFZbobxexu/qd2Z9dO1y4yc18/ixUviqDR1b71Sv355nhLlsX662vf5n3soWbp0aZu7HiN/i1sqMzrh+DPPX7sVUGrG279//yanKR/BN0b8XZHXVRK1CSdNmtRiIfPSSy+lnuT111/v7EUAugnlRXUNHDgwjRkzJuVo2rRp3f5CgvXTtcuMnNfPjBnvdPuT3uiSZ9SoUSlHOayfrvq9AqxombFs6NCUendso1wBYCN9+vQp7pv7sSx/rhT4tfd1lYwdOzatvvrqFZ+7//77i6vU8X65Hkw2Fp83DszjO2nue6Pnif48y4N1UF7URkvdZ3Rno0ePzqIGYK5qvX46oszIef0MGzY8gxpm1g+tE7V44kQ+tvtca43S/tYEudb0pnZlxpROaOGo5GqimW6pRl8l5c+Vmvy293VNXSmOWyW9/y8hjoPJpqbJVRyY97TPTPMiVLdNUInygtZywN61ddT6UWa0jxCka7N+ave9GsyRctG6zzZBm8uMqCDWwRehsx8EpK3WWGON4n7mzJlNhnmlZiKDBg2qH/Cjva8DAAAAgFoSADay0UYbFbXsYrCNf//73xW/tNLfN9544/pmHe19HQAAAADUkgCwkZVXXjltttlmxePrr79+uS9s9uzZ6bbbbisev//971/h1wEAAABALQkAKzj00EOLGnqPP/54+vnPf57mzJlTPzrvqaeeWoR5MVDHLrvsUpXXAQAAAECtGASkgk033TR97GMfS5dffnm66aab0s0331x0Qr1gwYL6ATyOP/741Ldv36q8DgAAAABqRRLVhKjNF7X1rr766jRp0qQixBs6dGjaYYcdiudWW221qr4OAAAAAGqhxwWAF154YaqrqytG4m1JhHZxi4E9Fi1alAYOHNiq92jv6wAAAACg2npcABi18doqRvdtT4jX3tcBAAAAQLUYBAQAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQAByEavXr3SwIEDi3sAAAD+v77/dw8A3d6AAQPSmDFjOnsxAAAAuhQBYDe1bNmyNHv27NRTPuvQoUPTwoUL0+LFizt7cehClixZ0mP2g9z16dMnDR48OOVo3rx5aenSpak7s366Nuunax9j5Lx+4nuL77A76927d3HxKEc5rJ+upK6uLg0aNKgoK+IYFEqWLl2W5s+f7wuhTWVGPN/RBIDd+GAlDlh7ggULFqRp06al4cOHF037oCTCv56yH/QkN9xwQ7HPd2ejR49O+++/f/E41xP/XFg/PXv9OMZYMbkGZ7mwfqorTuJnzJiRhgwZkvr161fludOdRfgXQQ+0pczoNW9epICpIwkAAehSIvybOnVqZy8GAABANgwCAgAAAAAZEwACAABAs3r9XzO+Xr4noFvSBBgAAACa0a9f3zRq1CjfEdBtqQEIAAAAABlTAxAAAIAu7cEHHyxG1OzOhg0blsaPH9/ZiwH0UAJAAAAAurQI/958863OXgyAbksTYAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMta3sxegq/rLX/6SnnrqqWan+chHPpLGjRu33N+XLl2a7r333jRp0qQ0a9asNGLEiLTVVlul97znPalXr141XGoAAAAAaEgA2IS77rqrxQBw1113XS4AfOONN9Kpp56aXn755QZ//+Mf/5i23HLLdMIJJ6SVV1652fkCAAAAQLUIAJvw6quvpn79+qUvf/nLTX5566+/foP/L1iwIH3zm99Mr7/+elpllVXSPvvsk0aPHl2EgTfffHN67LHH0jnnnJNOO+201Lu31tcAAAAA1J4AsIL58+enGTNmpPXWWy+9//3vb/WXecMNNxTh30orrZTOPffcIvwr2WmnnYraf48//nj65z//WfwfAAAAAGpNNbQmav+FsWPHtunLjFp+4YADDmgQ/oVoKrztttsWj2+//fb2ri8AAAAAaBM1ACt47bXX6gPAJ598Mj388MPp7bffLmr2bbLJJmmHHXZIffs2/Oqi5l/0/xd23HHHil/2Fltske6///5insuWLdMMGAAAAICaEwA2UwPw1ltvTZdccslyzXzXWGON9PWvf71BH4DPPvtscd+/f/+0zjrrVPyyN9hgg+J+4cKFafr06WnUqFHVW5MAAAAAUIEAsJkAMO4jzNtjjz2KkXsnT56cbrvttqKGYAz2Ef38rbnmmsW0M2fOLO5HjBiRevXqVWm2aejQofWPY/qmAsAYTCRCwkqi5mCoq6srpusJFi1a1OAeShYvXtxj9oPcRbk5YMCAlKMoz6PM7s6sn67N+unaxxg5r5/Fi5fEUWnq3nqlfv3yPCWyfrq2PNYPYenSpcV5CSy/j//nfjmdcH6Q569dlQLAaMr71a9+tRgNOOy+++5p3333Td/4xjfSrFmz0kUXXZS+9a1vFc/NmTOnuB80aFCT8y0PAJs70JwyZUqaNGlSi4XMSy+9lHqSaGYN5GngwIFpzJgxKUfTpk3r9kG19dO1WT9d+xgj5/UzY8Y73f6kN47zc22VY/10bTmsH6B1+3olyyIf6t2xw3IIACs4+OCDi5O17bbbrj78K4kagUcccUT6+c9/nh555JEi+BsyZEh9zbzSfVOhXf0X36gPwXLR9+Dqq69e8bnoQzDCwz59+mR7MNlYfN44MI/vJJpYQ8m8efPS4MGDfSEZaKrmdA5iUKgcagDmyvrp2eunI44xct5/hg0bnkENJuuna7N+6B6tPXKt6U37Rc2/CP/it7JSTfMpndDCUQBYwfjx45v90rbccsv6sC+aA2+44Yb1IcTcuXObfF15DZAIDZu7Uhy3Snr/X0IcB5NNTZOrODDvaZ+Z5sVVU9sEXZ0Dwq7N+unaOmr9OMZon1ybzubC+unarJ98LFmyZLmKQ1C+r1fcPqIGcAdXEujY+oaZqLTyVltttfq+/Zqqyl0aJThq7+Xa1AAAAACArkUAWKGJ7TnnnJMuu+yyJr+0qVOn1tfCi6YpYdy4ccV9hH9N9d9X+nuMHuwKAQAAAAAdQQDYSDTrveuuu9K1115bDPRRyY033ljcb7DBBsXowCH6jon+AcPf/va3ivMt/X2HHXao7loEAAAAgCYIABvZeuuti9F6o1Poc889N82ePbvB8zfccENRSzAceOCBDZ474IADivtbb701/fOf/2ww+MeFF15YjNob8957772bWh8AAAAAUFV67q3Q2fRxxx1XhH+PPfZY+sxnPpM23njjNGjQoPTiiy8WI8WF3XbbLe20004NXrvnnnume++9Nz388MPpzDPPLGoIjhw5Mk2ePDlNnz69GMDj2GOPra81CAAAAAC1JgCsIIK9qKl30UUXpSlTpqTHH3+8/rn4e9T0O+igg5Z7XfQJ+I1vfCNdfPHFRS3ACP7iVmoiHGGi5r8AAAAAdCQBYBO22GKLdMEFF6SXX365uEW4F7X51ltvvWIU36b079+/qOV3xBFHpOeffz7Nnz+/GPE3Xhc1AAEAAACgIwkAW7D22msXt7aKmoIRIgIAAABAZ1IlDQAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMhY385eANpn2bJlafbs2T3msw4dOjQtXLgwLV68uLMXhy5kyZIlPWY/yF2fPn3S4MGDU47mzZuXli5dmroz66drs3669jFGzusnvrf4Druz3r17pwEDBqQcWT9dWw7rh/9v6dJlaf78+b4OGqirq0uDBg0qji/ivLXS8x1NANiND1bigLUnWLBgQZo2bVoaPnx4GjhwYGcvDl1IhH89ZT+g+8r1xD8X1k/PXj+OMVZMrsFZLqyfrs36yUeEfxH0QLkI/mbMmJGGDBmS+vXrlxrrNW9epICpI2kCDAAAAAAZEwACAAAAQMY0AQYAAADa5cEHHyyaOnZnw4YNS+PHj+/sxYCaEgACAAAA7RLh35tvvuXbgy5OE2AAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgY307ewEAOtoNN9yQpk2b1q2/+NGjR6f999+/sxcDAACAbkAACPQ4Ef5NnTq1sxcDAAAAOoQmwAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABnr29kLkKvp06enF154Ic2cOTONGDEivfvd704DBw7s7MUCAAAAoIcRAFbZokWL0oUXXphuv/32tHTp0vq/Dxo0KH3kIx9JhxxySOrVq1e13xYAAAAAKhIAVlFdXV0688wz00MPPVSEfO95z3vS6NGj0yuvvJImTpyYLr/88jR79uz02c9+tppvCwAAAABNEgBW0d13312Ef717904nn3xyGj9+fP1zt912Wzr//PPTddddl3baaae08cYbV/OtsxZhajSf7k41J2+44YY0bdq01J1FeL3//vt39mIAAADQTg8++GCaMWNGt/7+hg0b1iBfoX0EgFV09dVXF/d77rnnchvnHnvskW655Zb0zDPPpJtuukkA2AYDBgxIY8aMSd1JhH9Tp07t7MUAAACgB4vw78033+rsxaALMApwlcyaNSs9//zzxePddtut4jRbb711cf/II49U620BAAAAoFlqAFbJ008/XfQBGM1/N9xww4rTbLLJJsV9jAwct1VWWaVab9/t5VAtee211y5Gey41n+3uusNn6NOnT7afrSd8hpw/Ww6fIefPlsNnyPmzdeRn6OhuRqr12Sot76hRq6aOaoaVqxw+Ww6fIefPlsNnyPVzrchniAygK+vp64f/6FUXqRUr7MYbb0y/+MUv0qqrrpouvvjiitO89NJLacKECcXjH//4x2n99devON2CBQvSwoULKz53//33FyMNR7PYnXfeuVuvuTh4jc8BAEDrPbPlVqluwYL//KFfv7T2+ef5CgHI3uLFS2II1tQdlnPGjHfSsGHDU79+y9e9e2jRorQopeJCZHQZ1xHUAKySOXPmFPcrrbRSk9MMHTq0QcjXlClTpqRJkyY1+35Lly4tAsXuLK6UrLfeeu2uxQUAAAD0DMuWLUtvvfVm0fqyu5gx452Kf18W+VAH1x4VAFZJ1Mprqfpv+XPNTTd27Ni0+uqrN1sDMEKz7jYwRiWLFy9OS5ZEgt+0eH769Olp5MiRqW9fmyz/ETVl1SJFeUFrKTPI+Rjj/9eIoHrf5+LUr18/Xyj1li1dmmbNnpVWHrpy6q0CA8qLTlJXtLrsDha3UANwyv9lSB2pex/pdCGlEGLu3LlNTlPerHfw4MFNThdVQONWSSk4LPVZ0xNEuh81JiP0FPZQrtQcHpQXtIYyg5yPMSqdXNB+S5ZEAOg75T8Wp7oiGO7dp7dtA+UFrRa/JRUvKC1eHAciqSN17d4qu5G4chxmz57dZHXUuMJcMmrUqA5bNgAAAAB6LgFglUSz3TB//vw0derUJvv2C2uttVYaNGhQtd4aAAAAAJokAKySGMxilVVWKR7fd999Fae59957i/utt966Wm8LAAAAAM0SAFZJ9M239957F4///Oc/p1dffbXB83//+9/To48+WvQxU5oOAAAAAGpNz7ZV9JGPfCTddddd6bXXXksnnHBC2nPPPdOIESPSs88+m+6+++5img9/+MNZjN4LAAAAQPcgAKyiGNn31FNPTWeccUZ68cUX0zXXXNOghuABBxyQPvGJT1TzLQEAAACgWQLAKltjjTXSj370o6K578SJE4tBQWLE3+233z6tvvrq1X47AAAAAGiWALAGop+/bbfdtrgBAAAAQGcyCAgAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZEwACAAAAAAZEwACAAAAQMYEgAAAAACQMQEgAAAAAGRMAAgAAAAAGRMAAgAAAEDGBIAAAAAAkDEBIAAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZKxXXV1dXWcvBK132223pQULFhSPBw4c2CO+uthEly5dmvr06ZN69erV2YtDF7Js2bLUu7frGPyH8gJlBj2hzFg8bVos/H/+0KtX6jNsWGcuUpbbRnfaJugAdXX/Ofa0bdBg01Be0PYyY9H//Y5HrrPHHnukjtC3Q96FmigFgT3FkiVLOnsRgG5CeQFkXWassspyf1rqmn71+U5prHTh2baB8oJuWGYIALuZAQMGpJ4mUvNFixal/v37q+0FKC8AxxhAh3NOAtSizOjIjEcTYLq8mTNnprvuuivtvPPOaZUKV7wBlBeAYwyglpyTAN29zNB5FgAAAABkTAAIAAAAABkTAAIAAABAxgSAAAAAAJAxASAAAAAAZEwASJcXw2JvuOGGHTo8NtA9KS8AZQbgGAPobAO6YI7Rq66urq6zFwIAAAAAqA01AAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGN9O3sByN/s2bPTHXfckV555ZW0ePHitPrqq6f3ve99ae21127X/M4777w0f/78Zqc58cQTU+/evWu+LED1Pfzww+nJJ59M06dPTyuvvHLaZJNN0vjx41O/fv3aNb8lS5akxx57LP3rX/9K77zzTurTp0+x72+33XZpvfXWq/ia++67L/3tb39rdr677rpr2mGHHdq1TED7vP3228W+Gb/jYc0110w77bRTGj16dIfPsxbLAlTPsmXLit/zZ555Js2YMSMNGzYsbbHFFmnLLbcsjgXaY+HChcVxytNPP13Ms3///sW+H8cDa621VsXX3HLLLemRRx5pdr4f/OAH03ve8552LRNQHa+99lq66667ivu+ffumddZZJ+28885p+PDhbZ7XzJkz089//vNmp4njhU9/+tM1X5Zyverq6upWaA7QjH/+858VA7tevXqlD3/4w+lTn/pU8bi1Yj6HHnpoi9Ndc801y/2wV3tZgOqaN29eOv3009NTTz213HPxo/eNb3yjzWH9q6++ms4888z04osvVnx+7733Tscee+xy5cXPfvazdPPNNzc770984hPpox/9aJuWB2i/v/71r+lXv/pVWrRoUYO/xwW/j3/84+mggw7qsHnWYlmA6omLiKeeemqaMmXKcs+9613vSv/zP/+TRo4c2aZ5Tpo0KZ199tlp2rRpyz0X+34cExx55JHLPfed73wnPfjgg83O+7//+7/Tbrvt1qblAarniiuuSFdeeWVaunRpg79HyH/cccel3XffvU3zi8oMJ510UrPTREWEyCdqvSzl1ACkZuJq27nnnlvUvtlggw2KDXXgwIHFzhC18CKkW2mlldIhhxzS6nlGAl764Y7QrimNa//VYlmA6vre975XhH8DBgxI++67b1p33XWLGjY33XRTmjp1ajrttNPSj3/842JfbY0FCxYUB91RO2fo0KFpr732SmPGjEmzZs1K99xzT1EuxEl81DKME/ZKZU2Eg6usskrF+Y8dO7YKnxpojQceeKAI5uO6ddSS2WWXXYor4lETJ/bnSy65pNiX99xzz5rPsxbLAlRPtPL59re/nV566aXi9z+OKaKW3uuvv55uvPHGNHHixOKY46yzzmp164JoQRDHFFHrL4LD2L/XWGON+prAETT+4Q9/SCNGjCjer/HFyKhk8NWvfrXJmocbbbRRVT470HY333xz+t3vflc8jhZC22+/fVGDOCoQPfroo+n8888vat5tvfXWrZ5n7PchjhGaajFU6ZymFstSTgBIzfzmN78pArfNNtusOHGPg+MQ4VucOF988cVFsh0/oK2tylrakTbddNOi6W5nLgtQPffff3/RRDfC+9hHo9lvyR577JEmTJhQXHGPsL7S1fVK/v73vxfhX/y4/uAHPyia/ZZ86EMfKsLEO++8M1177bVp//33b7DvR1kTV9mihmB7mwkB1REHvvE7HoFb/PZHNx+lGvtRPvz6178uyoaY5v3vf39xEaFW86zFsgDVdeuttxbhX1zsj5CvvPVAnIx/6UtfSpMnT0633357+q//+q9WzTMuRkb4N2rUqPSjH/2oCPlLolJCtGCIk/PLL7+8OJ8oBYtRgyeOX+J1USYAXcuCBQuK/bbUFP/oo4+ufy7OA+IcIs4pLrzwwqJJb2tbDJZyi/e+971pxx137NRlKWcQEGoifnRLzfiiXXspcCuJk+1BgwYVV+iibXtrlXakqBnU2csCVE+puW2cUJeHfyFq4MWPXogau6117733FvdR8688/AvxgxlNeEPs+0888UT9c9GkL5oOxQmD8A86X1wcePnll4sLBJ/5zGeWO+A9+OCDi+ein9+onVfLedZiWYDqirAu7LPPPst1HRI1AaMfrRABYFuPKSLsKw//QhwrfOxjHysex77/7LPP1j/35ptvFpUQ2nLuAnScf/7zn0V/fZEHVKpkEL/rpRwi+v5sa27RlhZDtVqWcgJAaiIOkENc7Yomt41FCBe1+EI0w22tUrO86GQ3au5EE5xIwuOKe+k9O2pZgOqIq+OlkD6uklUSHXaHt956q74caEmpj57oMqCSaMITtfxKB+wl0UQoavnED/bzzz+fLrvssqKc+clPflKcVMyZM6eNnxBYEaXf8fgNj9/yxoYMGZLWX3/9BtPWap61WBageqKbj7j439wxRQwEUurTLwb1aMsxRVNNdaM5cPkyVAoB4lgnagfHMUWcw0QA2dr3B2rjX//3Wx3nGhG8NRbdB0XT/vbkFnGeEccFN9xwQ9F094c//GH6/e9/X7Fv0louSzlNgKmJ0pWv0kFwJePGjSs6xC2NntcapR/R6IA3TtLLRZObaAsf/WtEfx+1XhagOqJ/v9LgPE3tp7GPlsR+Wn6g3ZSo8Ru1+5oaVS9q8ZQ68C8/kS+VM3GgHtXsIwwsd+mllxbNh4wADB0jTtJb+h2PQC6a9LX2d7y986zFsgDVE/toaYzL6GC/klKFgPh9j9/8pqYriem+/OUvN1ub54UXXqh/vNpqqy13TBGtjP74xz8u1/ohjimiK4HGrR+AjvFsK7KCeC76+2zt73qUQaXRe6Mbo6jV13iQj/322y8dddRRDVob1WJZGhMAUhOlK1/Nja5VCuka7xDNKf2IRvgXJ9/bbrtt8f9HHnmkqJof99EHx/e///36vjdqtSxAdZTvd6uuumrFaeIqWPyIRjOa1u6n0XFuUyIYjL4zSk2MS7UBysuZuNofyxP9A8XBfPw9Bg2JjsBjZOHoYHyrrbZq9ecE2qe0zzf3Ox5X2BvXvKnFPGuxLED1lPbROLZvqg/O0j7a2v00mvU31/f4vHnz0kUXXVQ8XmeddRqcvJdaLcS5S7Rgim5Jos/hF198sTimiBP5OJ6I44ryi51Ax5j1f2VAU+cg7ckKosVSVDKIW5y/xLnExhtvXJQVcTEgmu9GrcB4PgLCWi5LYwJAaqLUnK5S1dXGP76lGjgtiR2mtKF//vOfb9Bpb/yYRk2dqFYbI3vFFbXoOLNWywJUT6lJbRxgl5rkNrWfRgfcK7qfRs2/GAAkrrLFe37hC18oOgpvHABGM59TTz21wYlC9Bn6zW9+szhwj+Y7v/jFL/QTCB1URpTvp00dELe2OV1751mLZQGqpzXH/eUthVb0mCJqHMagIHFsEccwX/ziFxv0DVo6pohKC//zP//T4DgnRgv+xje+UfQT+Mtf/rJo4QR0rDmt+F1va1ZQ2u/jIkTjwQ2j5l90XxaDEN5yyy3FoKTvfve7a7YsjQkAaZfosyKazDYWo15ts8029VXvGzedK1d6rvGgHE2JH9Ovf/3rxYiepf7AysWoXvfcc0+677770j/+8Y/6ALAWywK07WD8pz/96XJ/j5p3xx13XP0+WtpfmxrRKvoKXJH9NJoZR/Ob+MGNmoTx/tGkp1STuCR+iKNmXzQdLg//QnT8feyxxxYH8VFDMC44aLYDtVX6jW7ud7xUPpRq/9dqnrVYFqB6WnPcX9pHV+SYImrqxGidUYsv3itaCpxwwglFLZ9yMWhIjBAexxWNL3LGaz71qU+lc845Jz3zzDPpjTfeaNB8GOhaZUbfVpYXMdhQ5BajR49ebgyCOM/55Cc/WQz4Eft85BalALAWy9KYtIN2iY7xY6NtrDSYxuDBg4v7uXPnNjmPUp9fjU+wmxJX8pqrfh8iGIwAsJS612pZgNaLWjCVyovSQW7pKn382EVN3wj5m5pP4yv3rRU1hONqWzS1iVp/cbEifnwbj+QXSj/CTYnn48rcggULirJGAAi11Zrf8dgf2/I73t551mJZgOppyz7anv00jlWipVEMEBa1deIk/EMf+lA6/PDDK9Y6LO9ipJLySg3Rp5cAEDrWoEGDivKiNWVGa89Bom/xSgOFlUS/f5tttllRqao8t6jFsjQmAKRd4kpWpZPeUp8XpR+vaP/elKjuHlrTmX9rVUrCO2tZgFT/AxVXwRorVW+Pq2Ml06dPrxgARr97paruq6++equ/2viRjOa+pQAyDsQ/85nPtNjhd3Piyl2pw96maisC1RO/4zGqZ5QPTYmr6G0pH9o7z1osC1A9peP+uLgfAV2lgK+0j7Z1P41af2eddVb9SJ077rhjcTFxRc4fys9dHFNA55QZL7zwQquygmr+rldqJdARyyIApF3i5Lm5E+joxPbWW28tqrPHlbKocdNYaZSbd73rXa16z9/97nfFQXfUAtx5552bHE00lP8Q12JZgNaL/i+aq70b+2tcsY/af//+97+LIe4bK428GdNFB9utEVXkv/vd76YnnniiCCGj79CWahE/99xzRTPh+FGOEcUriRP/0pU5J/hQe9F85qGHHirKh6aUyojW/o63d561WBageqIyQhzrxzF/dLQ/fvz4Jo/7Y1CO1taiiUCx1AdwdNAfXYi0VLvv0UcfLZoIjxgxIn3uc59r9twlOKaAjjdu3LgidHvqqaeaPJ+I84O2/K7HuARRceGggw5KG264YcVpIteolFtUe1kaWz4JgSqIPrXixzdO6O+///7lno+qrvGjHGI039aIGkBRi+f666+v+Hy81x133FE83nrrrWu6LED1RG266Ds03HnnnRWniSryIQ7kS7XvWhIH3RH+RY3CM844o8Xwr1T1PsqZaDIcFw0q+ctf/lLcx0lDDBQC1FbpBD5G0ay0X8bfoulc/NZvv/32NZ1nLZYFqJ7o2qN0YtzUMUXpfKEtx/1/+tOf6sO/6LOvpfAvxPFKHFPceOONRb/BzR1TRBgpAISOt9122xX3kQfEb3tj9957b5EjRCWE1uz3pWA/9v2//e1vFZ+PkK+UP5TnFrVYlsYEgNREVF9973vfWzy+8MILi4PhkuiDK34448pcbPClZsMtiUE+SgfXl156aYMOfGNHOO+884rBBmKH2GeffWq6LEB1Rf850fQl9u8rrriiwcAgMWhH/ODFgfRHPvKRVs/ztttuK+6jg+1KtQqb6rS3dKUuypTyfjlC9DF63XXXFY9joCGd/EPtxT4Zg/KE888/v0Hz29dee6240h522223NHLkyJrOsxbLAlTXAQccUNzH4IAxymZJnDtcfPHFRQ3AuOAXo3G2RpwnlC5EfuELX2j1vh1lRQSG8fpzzz13ua4DYtnigmNoy/ENUD3jx48vjv+jfIjf8NJIvCFq28UI3WH//fcvWjW1JbeI8L+0j5c34Y3uieJcJ85PygcjrMWyNNarrvwsC6ooauz993//dxGyRf8W0XF+nMBHldaoEjts2LAifCvv/ytEWh6j4YQYabPcz372s6Lj3RAjeEZTnNhB4oc8QsC44h7vWdrpVnRZgI7zm9/8Jl199dX11eHXXnvt9PLLLxcn1eFjH/tYOuywwxq8JkbzjYPq8IEPfKD+ylns89EvT4gf1sYj7zUWJwHRGW/pB/bkk0+uL1PihD/Km1iOUlOdKEOiebEAEDpGhPHRLD+a38dBb4y0WWriF+VA1JyJsqDxwD5xgv3II48U/YBNmDChKvNs7+uAjvODH/yg/sQ7TrLjGL/Ut1ZccIzyIAYEKxfHDqUT7LgwWervfPLkyen4448vXhe1Blvqqy+OVdZdd936ZsDf+c53irIhzkGidmK0TIjmf6UaPjHPb3zjG/oAhE4yceLEYh+M/TT2z2jhE/2Ix9/j9z2a5kb/n43PJ6666qqi24/43Y8KByWLFy8uziVKLQXi+SiHItCL3CLeJyotfe973yvmXY1laS0BIDUVCfdPfvKT9NhjjzWo0RNVVuMKWqWq7ldeeWW6/PLLi8elmjYlMY+oKh99dMWPdLmxY8cWO16pKWE1lgXoWNdcc02xf5df8YqAPg6m99133+WmjwD/ox/9aPH405/+dDrwwAOLx08++WQ66aSTWv2+0ZfP7rvvXv//CPp+9atfFeVF44FL9tprr3TEEUdUHO0PqJ24IBC17sqb3kZIH1fMo4/P4cOHL/eaX/ziF8UV+ChHfvvb31ZlnivyOqBjRAWBOJ+44YYbGoz6Gy2D4nxhp512Wu41Ee4fe+yxxeMTTjghvf/97y8eR5AYgWJrnX766Q1G940T94suuqi4LxcXJqI1wcEHH1xxIEOg4zzzzDPppz/9aZoyZUr932K/jLEHjjnmmPoRxstFgBddjEWlpFILgJKFCxcWZVBUXiovg+ICwuabb56OOuqo+gsF1ViW1hIA0iEifIuD5djgo1prc0Pcx3Sljb2pPrviRz2u4kVV+rj6HrWFWlt7ry3LAnS8CPWef/75okl/nLTHj2NTNe3iSlg0Dw4xXfShE+IKf+MD7eZELb9KZUGUMVEeRZkTtQBj8CO1/qBzRW3cuEVN/qgp3FxzvChLYtq4Ul5pMID2zLMarwM6RgzeEecMUWM3muNGLZym+hKOk/SHH364eBw19WL6UjAY82itaPobxy+NRT+ApZYEcZEgjlta268x0DGmTp1a7Ktx0T8GHozj/6ZEUBfnChHmN9UnXwSB0booRhGPGn1RBjU3z/YuS2sJAAEAAAAgYwYBAQAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQAAACAjAkAAQAAACBjAkAAAAAAyJgAEAAAAAAyJgAEAAAAgIwJAAEAAAAgYwJAAAAAAMiYABAAAAAAMiYABAAAAICMCQABAAAAIGMCQAAAAADImAAQAAAAADImAAQA6EIuueSStO222xa3N954o8Fze+yxR/H3I444ouJrly1bli6//PJ0+OGHp5133rmYdvr06fXPT548OX3ta19Le+65Z9puu+3SD3/4w1Yt02WXXVa/TPfee+8KfkIAADpa3w5/RwAAmvTaa6+lhx9+uHi8aNGiBs899thjRaC3ZMmSiq897rjj0oUXXtjgb4sXLy7un3zyybTDDjukuXPn1j+34447tmpNvP766/XLNHPmTGsPAKCbEQACAGTgnXfeSRdffHHxeM0110wXXHBBGjNmTFp11VWLv/385z+vD/++/OUvp49+9KNp7NixnbrMAAB0DAEgAEA3cfvttxc1+gYPHrzcc88991x9zcDDDjssfeQjH2nw/MSJE4v7Xr16pbPOOisNGDCg1e/78Y9/PO26667F44022mgFPwUAAB1NAAgA0E1sscUWTT43Z86c+selWn+Vnh86dGibwr8wevTo4gYAQPdkEBAAgMwMHDjw/7V37zFV1mEAxx8SEtDMYN5gpCxKY5YRU2sqbjYvy5YmU9Mxh2WYOtJcNpu02frDFhPoYmVAWU2bDiGdl8hNTd2cmpmKl9SZChpeY9oUKX3b89vedwc47+FA54gevp/tnT/f6++85/zBnj3P72nRMQAAAIQmMgABAADuoNraWikpKZGNGzdKZWWlCcj16tVL0tPTZcSIET6v1S7ANTU10rt3b9Pt1+4arOv9Xbt2zTkvPz/fOa5lweHh4XL06FHz/ytXrphuvmry5Mkyd+5cv7oAFxQUmLE+69lnn/V6rLy8XGJjY+Xnn3+WsrIyOXLkiFl3sGvXrpKWliZTpkyRmJiYZr+zBQsWmHtr6fO2bdtMGfTatWvNdubMGWnXrp307dtXMjIynM/W0Lp162ThwoVmvHLlSnnkkUdk9+7d5vMcP35c3nnnHRkzZky9a65evSqrV682pddnz54Vy7IkISFBnnvuOZkwYYLXUuxAzdczc3PFihWydetWqaqqMvv0fWoDl4kTJ0p8fHyz3ycAAGiDLAAAANwRBw8etPr06WPpn2Detueff97Kyclx/l9ZWVnv+tjYWLO/X79+zr5Fixa53q+pbfbs2X7NOzc317lm48aNrsf0840cOdL1eXFxcdZvv/3W7Pc2ceJEc32HDh2siooKKzk52ev9w8LCrBkzZlj//PNPo3t8/fXX9eZZXFxstWvXztlXWFhY7/ySkhKrW7durp+le/fuVllZWdDmqzZv3mye4zaH6Oho67PPPmv2+wQAAG0PGYAAAAB3gGb7aYbfn3/+6TTq0E0z5g4cOCC5ubmyYcMG2bRpU7Pum5mZaTID9+7dK6+//rrZp9lsdhMQOwNw6tSpUlFRIT169DCZaCrQ6/oNHz5cqqurZciQITJjxgyT2ajdib/88ktZs2aNnDt3zmTOHT582GTBNdfNmzdNM5LLly+b7De9l653qNmNH330kbmvdjvWzD3NTHSj73jevHly69Ytr8eXLVsmr776qty+fVsSExPljTfekKeeespk8v3yyy+yZMkSkxGo73jp0qXy2muvBXy+hw4dktGjR8uNGzdM4xXN1Hz88cfNnPbv3y+ffvqpnDhxQmbOnCkPPvigyeYEAABw1doRSAAAgLbgxRdfdDK3ioqKGh3/66+/TGafZ4aXPxmAti1btjjXff75542ODxw40Bzr2bNns+fubwagnVV4+/btRvcYNmyYc86mTZua9Xw7o87e8vPzG51z/fp1Ky0tzTlHM/jcMgA7duxosu8yMjKs0tJSa9euXdbFixfNeYcPH7YiIyPNeSkpKVZNTU2jZ50/f97J6ouIiGiU1RiI+U6YMMHs79Spk3leQzqvxMREc05CQoLXdw4AAGCjCQgAAECQ7du3z8m6Gz9+vMkua6hz587y7bff3tPfRWpqquTl5UlYWFijY56fWbMVW6p///4yZ86cRvujoqJMpqGdWagZlb7W1SsuLpbvvvtOXnrpJRkwYIDTOVnXCdR1GtVXX31lsusa0jX49FlKswLff//9gM9X11FUulagPq8hndf06dOd7NJjx465zgEAAIAAIAAAQJB5Bvays7Ndz3vyySfrNdi412iTj/vu8/7npZax2i5cuNDiZ7iV2yptjjJ48GAz3rVrl1y6dMnreaNGjTIl0Q1puXJpaakZaxmzlv26GTRokGkkotavXy91dXUBna82T1FaHq6l095kZWXJnj17zKbNSQAAANwQAAQAAAgyO5urffv2TQb47uUA4KOPPup6rGPHjs7YLVjmDw28+aLdhj0zL70ZO3as1/07d+40ayaqkSNHNjmXoUOHmn81Y1DX5QvkfDVz0M5WHDhwoMkWvHjxYr1rH3roIdNFWDe3jsQAAACKACAAAECQabMH1bNnT9OQwxc9517VoUMHv86zLF26rmWSkpJ8Ho+Pj3fGDQNmNrfmJ0eOHHHGWnrbFM/S3PPnzwd0vosXL5ZOnTqZcVVVlSn31Xlrlqg2JdGS8uvXrzc5RwAAAEUAEAAAIIi0i6t2g1V2QCcQQbS7kVv5b6BERkbK/fff7/MczzX77LX8/KUlwLaYmJgmz3/ggQecsbdg3P+Zb0pKiuk4nJ6e7gSNNXB68OBB+eSTT2TMmDHSpUsXmTZtmtNZGgAAwA0BQAAAgCCymzz4W/pKVpe7iIgIvwKuniWyLeVPlmJ1dbUz9tYs5P/OV0uqS0pKzHOWL19uGql4ZhTqb0WbmWiJ8OXLl5t8FgAAaLsIAAIAAASRZoDZmWJuzRw8kc3l7tq1a6brrr/vz+7s66/Y2NgmS3o9eX6fDz/8cNDmq/OaPHmyFBUVyfHjx+XUqVOSn5/vlDJrF+CPP/64yfkCAIC2iwAgAABAkNndZLXL6+nTp32eu3fvXr4PHzzX6fNGy2btzEtfXXy90fX1Gt7Hza1bt2T79u1mrAFe7egbqPn+8MMPTnMPb9frOpFz5syRH3/80dnH7wYAAPhCABAAACDIRo0a5YxXrVrlet6FCxdky5YtfB8+rFu3zvVYTU2NlJeXm7EGzzzX6PPHM88843Qr1tJbDfK52bp1q/m+lK7T57b+YUvmq/9qQE+3PXv2uF6vAUP7mmCvvwgAAO5t/KUAAAAQZNqoITo62ozz8vJMJqA3b7/9dpMlo22dlr66rXc3f/58Zw3F7OzsZt9bG7C88sorZnzy5En54osvXM/98MMPncCbduUN5HwHDRrkNIwpLCx0XY9Qu0trmbHq37+/H58QAAC0VQQAAQAAgqxr166Sm5trxtrQYcSIEbJv3z7nuAZxZs+eLd98841ERUXxffigwdNhw4bJr7/+6uy7evWqKYldunSp+b82xZg0aVKL3uN7770nCQkJZvzmm2+aAJ5nYxb9/jIzM+Wnn35yAnfasTeQ89Xuwfp7UDt27JCMjIx66w1qQHDDhg2mE7DdgCQrK6tFnxcAALQN4a09AQAAgLZg5syZplnDBx98YIJ/Tz/9tMTHx5vOr5ptpkGmxMREeeutt2TWrFmtPd271rhx46S0tFRSU1MlLi7OeX92N93k5GRTdtvSktjOnTubslwN0lZVVcncuXMlJydHevXqJTdv3jRrOP7777/mXA3aLV68OCjz1WfqGoNaarxixQr5/vvvze9DA8T6O9IgotLMUi0rtxuCAAAAeBNmudUUAAAAIODWrl0rCxcurJcB2KVLF9PlVbPP9E+zEydOmP39+vWTiIgI57z9+/ebEmEN+mjgyJNmEf7+++9Okwi9p6ejR4/K33//Le3bt5cnnniiWXPWjrgadFKPPfaYU57a8FifPn2cNfQaqq2tlYqKCicj0lvXXDcvv/yyrFy50ow1UFpcXGy63mpHXJt+Xi21XrBggSnlbUjLcP/44w8zTkpKMoE+X3R9vkWLFsny5cvl7Nmzzv7w8HAZPHiwyfzT4F6w5qvq6uqkoKDAXH/s2LF6xzTr74UXXpB3333XtQEJAACAjQAgAABAK9AGEho800CUZgLSxMGdZ0BNM+e0RFbp+9P3qAE0zY4LCwsLynel5bdayqvBzR49ejRZph2M+V65csVcrwFg/c1omXKwPi8AAAg9lAADAAC0As2C0w0tp2Wvd6L0VUt3dWvN+cbExJgNAACgJWgCAgAAAAAAAIQwAoAAAAAAAABACCMACAAAAAAAAIQwmoAAAADgrnby5EnTBEOlpqbe9c0v7rX5AgCA0EcAEAAAAAAAAAhhlAADAAAAAAAAIYwAIAAAAAAAABDCCAACAAAAAAAAIYwAIAAAAAAAABDCCAACAAAAAAAAIYwAIAAAAAAAABDCCAACAAAAAAAAIYwAIAAAAAAAABDCCAACAAAAAAAAIYwAIAAAAAAAABDCCAACAAAAAAAAErr+A0kJB9J9wrBWAAAAAElFTkSuQmCC",
"text/plain": [
- ""
+ ""
]
},
"execution_count": 6,
@@ -326,7 +326,7 @@
},
{
"cell_type": "markdown",
- "id": "fbe81337",
+ "id": "d57e39e1",
"metadata": {},
"source": [
"See {doc}`guides/plotting` for shading, confidence-interval overlays, theoretical\n",
@@ -338,7 +338,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "4572f5a6",
+ "id": "11af0077",
"metadata": {},
"outputs": [
{
@@ -382,7 +382,7 @@
},
{
"cell_type": "markdown",
- "id": "4f5f8ecc",
+ "id": "ad24a1df",
"metadata": {},
"source": [
"Full details in {doc}`guides/regression`."
diff --git a/doc/_build/jupyter_execute/guides/confidence-intervals.ipynb b/doc/_build/jupyter_execute/guides/confidence-intervals.ipynb
index 6b7d0d6..44a4c6c 100644
--- a/doc/_build/jupyter_execute/guides/confidence-intervals.ipynb
+++ b/doc/_build/jupyter_execute/guides/confidence-intervals.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "698ef2fc",
+ "id": "6b92c300",
"metadata": {
"tags": [
"remove-input"
@@ -19,7 +19,7 @@
},
{
"cell_type": "markdown",
- "id": "1b461e74",
+ "id": "abcfc89e",
"metadata": {},
"source": [
"# Bootstrapping & confidence intervals\n",
@@ -33,7 +33,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "a378e970",
+ "id": "9de39318",
"metadata": {},
"outputs": [],
"source": [
@@ -51,7 +51,7 @@
},
{
"cell_type": "markdown",
- "id": "bb025ca7",
+ "id": "2feca301",
"metadata": {},
"source": [
"## Confidence intervals — three methods"
@@ -60,7 +60,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "a20822b6",
+ "id": "4c98a811",
"metadata": {},
"outputs": [
{
@@ -106,7 +106,7 @@
},
{
"cell_type": "markdown",
- "id": "81ff2349",
+ "id": "535eb1f0",
"metadata": {},
"source": [
"Distribution objects also expose the getter as a method:"
@@ -115,7 +115,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "2ade91e2",
+ "id": "fbbf65ea",
"metadata": {},
"outputs": [
{
@@ -152,7 +152,7 @@
},
{
"cell_type": "markdown",
- "id": "6816ee77",
+ "id": "55554090",
"metadata": {},
"source": [
"## Visualize the interval"
@@ -161,7 +161,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "2149339e",
+ "id": "ee541d51",
"metadata": {},
"outputs": [
{
@@ -169,7 +169,7 @@
"image/png": 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",
"text/html": [
" \n",
- " "
+ "
"
],
"text/plain": [
"Figure({\n",
@@ -233,7 +233,7 @@
},
{
"cell_type": "markdown",
- "id": "ec97d48b",
+ "id": "10ac42c3",
"metadata": {},
"source": [
"## A confidence interval for a proportion"
@@ -242,7 +242,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "c32aedae",
+ "id": "84da60b7",
"metadata": {},
"outputs": [
{
@@ -288,7 +288,7 @@
},
{
"cell_type": "markdown",
- "id": "2d2c260d",
+ "id": "68d7bf68",
"metadata": {},
"source": [
"## A confidence interval for a difference\n",
@@ -299,7 +299,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "7d3fbe60",
+ "id": "27b0d352",
"metadata": {},
"outputs": [
{
@@ -341,7 +341,7 @@
},
{
"cell_type": "markdown",
- "id": "1b2d5bb1",
+ "id": "a5e6b357",
"metadata": {},
"source": [
"```{seealso}\n",
diff --git a/doc/_build/jupyter_execute/guides/hypothesis-testing.ipynb b/doc/_build/jupyter_execute/guides/hypothesis-testing.ipynb
index c099abd..dd30961 100644
--- a/doc/_build/jupyter_execute/guides/hypothesis-testing.ipynb
+++ b/doc/_build/jupyter_execute/guides/hypothesis-testing.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "2b6e61a7",
+ "id": "d5b01ce5",
"metadata": {
"tags": [
"remove-input"
@@ -19,7 +19,7 @@
},
{
"cell_type": "markdown",
- "id": "8e6689ce",
+ "id": "be0ff29c",
"metadata": {},
"source": [
"# Hypothesis testing\n",
@@ -37,7 +37,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "ed4d9128",
+ "id": "d8682ec9",
"metadata": {},
"outputs": [
{
@@ -93,7 +93,7 @@
},
{
"cell_type": "markdown",
- "id": "8b3c180f",
+ "id": "3eb2ecb3",
"metadata": {},
"source": [
"## Shade the p-value"
@@ -102,7 +102,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "07048ee8",
+ "id": "73325766",
"metadata": {},
"outputs": [
{
@@ -110,7 +110,7 @@
"image/png": 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",
"text/html": [
" \n",
- " "
+ " "
],
"text/plain": [
"Figure({\n",
@@ -157,7 +157,7 @@
},
{
"cell_type": "markdown",
- "id": "2837f648",
+ "id": "66844467",
"metadata": {},
"source": [
"`direction` is one of `\"right\"`/`\"greater\"`, `\"left\"`/`\"less\"`, or `\"two-sided\"`.\n",
@@ -171,7 +171,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "f334b87f",
+ "id": "185fa827",
"metadata": {},
"outputs": [
{
@@ -218,7 +218,7 @@
},
{
"cell_type": "markdown",
- "id": "43b7ae1e",
+ "id": "d41ca0a7",
"metadata": {},
"source": [
"For a one-proportion test you can also *simulate* draws directly:"
@@ -227,7 +227,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "66d59339",
+ "id": "dea7cb9f",
"metadata": {},
"outputs": [],
"source": [
@@ -245,7 +245,7 @@
},
{
"cell_type": "markdown",
- "id": "d8161be1",
+ "id": "19440cbc",
"metadata": {},
"source": [
"## Available statistics\n",
@@ -255,6 +255,71 @@
"`\"diff in props\"`, `\"ratio of means\"`, `\"ratio of props\"`, `\"odds ratio\"`,\n",
"`\"slope\"`, `\"correlation\"`, `\"t\"`, `\"z\"`, `\"F\"`, `\"Chisq\"`.\n",
"\n",
+ "## Chi-square goodness-of-fit\n",
+ "\n",
+ "For a single categorical variable with several levels, test whether the observed\n",
+ "counts match a set of hypothesized proportions: `hypothesize(null=\"point\", p=...)`\n",
+ "with `p` a `{level: probability}` mapping, then `generate(type=\"draw\")` to simulate\n",
+ "from those proportions."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "fdc5d6b3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "shape: (1, 1)p_value f64 0.0
"
+ ],
+ "text/plain": [
+ "shape: (1, 1)\n",
+ "┌─────────┐\n",
+ "│ p_value │\n",
+ "│ --- │\n",
+ "│ f64 │\n",
+ "╞═════════╡\n",
+ "│ 0.0 │\n",
+ "└─────────┘"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gss = md.load_gss()\n",
+ "levels = gss[\"finrela\"].unique().to_list()\n",
+ "uniform = {level: 1 / len(levels) for level in levels} # \"all classes equally likely\"\n",
+ "\n",
+ "obs_gof = gss.specify(response=\"finrela\").hypothesize(null=\"point\", p=uniform).calculate(stat=\"Chisq\")\n",
+ "\n",
+ "null_gof = (\n",
+ " gss.specify(response=\"finrela\")\n",
+ " .hypothesize(null=\"point\", p=uniform)\n",
+ " .generate(reps=1000, type=\"draw\", seed=1)\n",
+ " .calculate(stat=\"Chisq\")\n",
+ ")\n",
+ "get_p_value(null_gof, obs_stat=obs_gof, direction=\"greater\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d5c985f6",
+ "metadata": {},
+ "source": [
+ "The one-line wrapper is `chisq_test(gss, response=\"finrela\", p=uniform)`.\n",
+ "\n",
"## Custom test statistics\n",
"\n",
"Beyond those strings, `stat=` accepts **any function** that takes the response\n",
@@ -265,8 +330,8 @@
},
{
"cell_type": "code",
- "execution_count": 6,
- "id": "e5b0a798",
+ "execution_count": 7,
+ "id": "b9276f8e",
"metadata": {},
"outputs": [
{
@@ -292,7 +357,7 @@
"└──────────┴──────────┘"
]
},
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
@@ -315,7 +380,7 @@
},
{
"cell_type": "markdown",
- "id": "4f5c5aed",
+ "id": "67193c64",
"metadata": {},
"source": [
"The function receives `(response, explanatory)` as numpy arrays (`explanatory` is\n",
@@ -363,7 +428,9 @@
82,
93,
109,
- 123
+ 123,
+ 134,
+ 148
]
},
"nbformat": 4,
diff --git a/doc/_build/jupyter_execute/guides/messages.ipynb b/doc/_build/jupyter_execute/guides/messages.ipynb
index 7adc721..dd52f93 100644
--- a/doc/_build/jupyter_execute/guides/messages.ipynb
+++ b/doc/_build/jupyter_execute/guides/messages.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "6d704923",
+ "id": "0ef2fe67",
"metadata": {
"tags": [
"remove-input"
@@ -17,7 +17,7 @@
},
{
"cell_type": "markdown",
- "id": "a684ea40",
+ "id": "7bc9b7cc",
"metadata": {},
"source": [
"# Helpful messages & errors\n",
@@ -43,7 +43,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "3f78feb2",
+ "id": "a17e6252",
"metadata": {},
"outputs": [
{
@@ -68,7 +68,7 @@
},
{
"cell_type": "markdown",
- "id": "f731bce1",
+ "id": "9b9e534a",
"metadata": {},
"source": [
"Pass the wrong kind of object and the error names the fix:"
@@ -77,7 +77,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "a0c82df4",
+ "id": "3ee652f5",
"metadata": {},
"outputs": [
{
@@ -101,7 +101,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "72095189",
+ "id": "129e3bda",
"metadata": {},
"outputs": [
{
@@ -125,7 +125,7 @@
},
{
"cell_type": "markdown",
- "id": "970ecd9c",
+ "id": "fe695854",
"metadata": {},
"source": [
"## Informational notes (and how to silence them)\n",
@@ -138,7 +138,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "9641342e",
+ "id": "c67e48fd",
"metadata": {},
"outputs": [
{
@@ -166,7 +166,7 @@
},
{
"cell_type": "markdown",
- "id": "47baad6c",
+ "id": "4804b53f",
"metadata": {},
"source": [
"These notes are designed to be **easy to turn off** once you know what they mean.\n",
@@ -176,7 +176,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "0c766bd6",
+ "id": "6ab8b088",
"metadata": {},
"outputs": [
{
@@ -197,7 +197,7 @@
},
{
"cell_type": "markdown",
- "id": "3cad8a4f",
+ "id": "d03d2970",
"metadata": {},
"source": [
"Or silence every moderndive note globally with a standard `warnings` filter:\n",
diff --git a/doc/_build/jupyter_execute/guides/plotting.ipynb b/doc/_build/jupyter_execute/guides/plotting.ipynb
index 4456d86..19f25cf 100644
--- a/doc/_build/jupyter_execute/guides/plotting.ipynb
+++ b/doc/_build/jupyter_execute/guides/plotting.ipynb
@@ -3,7 +3,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "id": "63a00682",
+ "id": "12170058",
"metadata": {
"tags": [
"remove-input"
@@ -19,7 +19,7 @@
},
{
"cell_type": "markdown",
- "id": "fafbaa35",
+ "id": "4d33fa9c",
"metadata": {},
"source": [
"# Plotting: plotly & plotnine\n",
@@ -42,7 +42,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "id": "ae862395",
+ "id": "0b999025",
"metadata": {},
"outputs": [
{
@@ -91,7 +91,7 @@
},
{
"cell_type": "markdown",
- "id": "d5f4de24",
+ "id": "894f35df",
"metadata": {},
"source": [
"## visualize() returns an InferPlot\n",
@@ -104,7 +104,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "id": "3ec8ce63",
+ "id": "f8cf16cc",
"metadata": {},
"outputs": [
{
@@ -112,7 +112,7 @@
"image/png": 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",
"text/html": [
" \n",
- " "
+ " "
],
"text/plain": [
"Figure({\n",
@@ -168,14 +168,14 @@
{
"cell_type": "code",
"execution_count": 4,
- "id": "44630eb6",
+ "id": "a25b42fe",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
- ""
+ ""
]
},
"execution_count": 4,
@@ -195,7 +195,7 @@
},
{
"cell_type": "markdown",
- "id": "d31f079c",
+ "id": "5a0845d4",
"metadata": {},
"source": [
"### Keyword form\n",
@@ -206,7 +206,7 @@
{
"cell_type": "code",
"execution_count": 5,
- "id": "44ec0cac",
+ "id": "153628b2",
"metadata": {},
"outputs": [
{
@@ -214,7 +214,7 @@
"image/png": 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",
"text/html": [
" \n",
- " "
+ " "
],
"text/plain": [
"Figure({\n",
@@ -269,7 +269,7 @@
},
{
"cell_type": "markdown",
- "id": "36ac5e12",
+ "id": "aa1bcba9",
"metadata": {},
"source": [
"## Shading p-values"
@@ -278,7 +278,7 @@
{
"cell_type": "code",
"execution_count": 6,
- "id": "9c45e737",
+ "id": "b2775ed4",
"metadata": {},
"outputs": [
{
@@ -286,7 +286,7 @@
"image/png": 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",
"text/html": [
" \n",
- " "
+ " "
],
"text/plain": [
"Figure({\n",
@@ -342,7 +342,7 @@
},
{
"cell_type": "markdown",
- "id": "0b654a2b",
+ "id": "9267a666",
"metadata": {},
"source": [
"## Simulation vs. theory overlays"
@@ -351,7 +351,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "id": "16ab67ec",
+ "id": "2bf00033",
"metadata": {},
"outputs": [
{
@@ -359,7 +359,7 @@
"image/png": 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",
"text/html": [
" \n",
- " "
+ " "
],
"text/plain": [
"Figure({\n",
@@ -391,7 +391,7 @@
{
"cell_type": "code",
"execution_count": 8,
- "id": "0e68f3c7",
+ "id": "7de1dc6b",
"metadata": {},
"outputs": [
{
@@ -399,7 +399,7 @@
"image/png": 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",
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