128 lines
3.0 KiB
Plaintext
128 lines
3.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import scipy as sc\n",
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"import pandas as pd\n",
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"from matplotlib import pyplot as plt\n",
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"from scipy import stats \n",
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"from IPython.core.interactiveshell import InteractiveShell\n",
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"InteractiveShell.ast_node_interactivity = \"all\"\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 52,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"KstestResult(statistic=0.0019255354784954437, pvalue=0.8515501507924718, statistic_location=-0.003026398265409117, statistic_sign=1)"
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]
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},
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"execution_count": 52,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"text/plain": [
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"KstestResult(statistic=0.0019317484822836684, pvalue=0.8488394389115358, statistic_location=-0.003041920835342991, statistic_sign=1)"
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]
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},
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"execution_count": 52,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"rng = np.random.default_rng()#(seed=1234)\n",
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"dof=100\n",
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"size=(100000)\n",
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"dt=15/365\n",
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"sqrtdt=np.sqrt(dt)\n",
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"sfactor=np.sqrt((dof-2)/dof)\n",
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"\n",
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"#np.sqrt(1/np.random.gamma(dof/2,dof/2,nsims))\n",
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"\n",
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"N=rng.normal(0,sqrtdt,size)\n",
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"W=1/np.sqrt(rng.chisquare(dof,size)/dof)\n",
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"T=sfactor*N*W\n",
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"\n",
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"stats.kstest(N,\"norm\",args=(0,sqrtdt))\n",
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"assert stats.kstest(N,\"norm\",args=(0,sqrtdt)).pvalue>0.05 #accept null of normality\n",
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"\n",
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"stats.kstest(T,\"t\",args=(dof,0,sfactor*sqrtdt))\n",
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"\n",
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"\n",
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"#stats.kstest(T,T1)\n",
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"\n",
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"#pd.Series(T).describe()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 50,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([0.04109589, 0.08219178, 0.12328767, 0.16438356, 0.20547945,\n",
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" 0.24657534, 0.28767123, 0.32876712, 0.36986301, 0.4109589 ,\n",
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" 0.45205479, 0.49315068, 0.53424658, 0.57534247, 0.61643836,\n",
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" 0.65753425, 0.69863014, 0.73972603, 0.78082192, 0.82191781,\n",
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" 0.8630137 , 0.90410959, 0.94520548, 0.98630137])"
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]
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},
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"execution_count": 50,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"days=np.arange(15,365,15)\n",
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"timegrid=days/365\n",
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"\n",
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"timegrid"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Main",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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