Created
September 16, 2019 08:51
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2項分布とχ^2分布の近似性
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{ | |
"cells": [ | |
{ | |
"metadata": {}, | |
"cell_type": "markdown", | |
"source": "# 二項分布とchi2分布の近似性" | |
}, | |
{ | |
"metadata": {}, | |
"cell_type": "markdown", | |
"source": "## Bin(n=10)の場合" | |
}, | |
{ | |
"metadata": { | |
"ExecuteTime": { | |
"start_time": "2019-09-16T08:47:15.283635Z", | |
"end_time": "2019-09-16T08:47:24.162817Z" | |
}, | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "import scipy as sp\nimport scipy.stats as stats\nimport matplotlib.pyplot as plt\n\n%matplotlib inline\n\nIter = 10000\nN = 10000\nn = 10\ndef plot(Iter, N, n): \n binom = stats.binom(n=n, p=1/2)\n chi2 = sp.empty(Iter)\n for i in sp.arange(Iter):\n b_r = binom.rvs(N)\n hist, bins = sp.histogram(b_r, bins=sp.arange(0, n+1+1))\n\n x=sp.arange(0, n+1)\n E_t = N * binom.pmf(x)\n chi2_ = sp.sum((hist - E_t)**2 / E_t)\n chi2[i] = chi2_\n\n plt.figure()\n x = sp.arange(0, n*3+1)\n plt.hist(chi2, density=True, bins=int(N/10), label=\"chi^2 from bin random\")\n c = stats.chi2(df=n+1-1)\n plt.plot(x, c.pdf(x), label=f\"$\\chi^2(df={n+1}-1)$\")\n plt.xlim(0, n*3)\n plt.legend()\n plt.show()\n \nplot(Iter, N, n)", | |
"execution_count": 5, | |
"outputs": [ | |
{ | |
"output_type": "display_data", | |
"data": { | |
"text/plain": "<Figure size 432x288 with 1 Axes>", | |
"image/png": 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\n" | |
}, | |
"metadata": { | |
"needs_background": "light" | |
} | |
} | |
] | |
}, | |
{ | |
"metadata": {}, | |
"cell_type": "markdown", | |
"source": "## n=50の場合" | |
}, | |
{ | |
"metadata": { | |
"ExecuteTime": { | |
"start_time": "2019-09-16T08:48:05.127430Z", | |
"end_time": "2019-09-16T08:48:24.612098Z" | |
}, | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "Iter = 10000\nN = 10000\nn = 50\n\nplot(Iter, N, n)", | |
"execution_count": 6, | |
"outputs": [ | |
{ | |
"output_type": "display_data", | |
"data": { | |
"text/plain": "<Figure size 432x288 with 1 Axes>", | |
"image/png": 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\n" | |
}, | |
"metadata": { | |
"needs_background": "light" | |
} | |
} | |
] | |
}, | |
{ | |
"metadata": { | |
"trusted": true | |
}, | |
"cell_type": "code", | |
"source": "", | |
"execution_count": null, | |
"outputs": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"name": "python3", | |
"display_name": "Python 3", | |
"language": "python" | |
}, | |
"hide_input": false, | |
"toc": { | |
"nav_menu": {}, | |
"number_sections": true, | |
"sideBar": true, | |
"skip_h1_title": false, | |
"base_numbering": 1, | |
"title_cell": "Table of Contents", | |
"title_sidebar": "Contents", | |
"toc_cell": false, | |
"toc_position": {}, | |
"toc_section_display": true, | |
"toc_window_display": true | |
}, | |
"language_info": { | |
"name": "python", | |
"version": "3.7.4", | |
"mimetype": "text/x-python", | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"pygments_lexer": "ipython3", | |
"nbconvert_exporter": "python", | |
"file_extension": ".py" | |
}, | |
"gist": { | |
"id": "", | |
"data": { | |
"description": "2項分布とχ^2分布の近似性", | |
"public": true | |
} | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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