Merge pull request #29 from alexanderlata/main

fix typos and add critical value for het_white
artamonoff · May 11, 2024 · 4d3da5b · 4d3da5b
2 parents d0719f4 f5bda67
commit 4d3da5b
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Showing 2 changed files with 70 additions and 15 deletions.
diff --git a/econometrica-1/jupyter-notebooks/diagnostic-het.ipynb b/econometrica-1/jupyter-notebooks/diagnostic-het.ipynb
@@ -9,7  9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
    "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -133,7  133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -143,7  143,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
    "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -164,16  164,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
    "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(44.53371850842671, 4.970083203924699e-09)"
        "(44.53371850842652, 4.970083203925146e-09)"
       ]
      },
-     "execution_count": 4,
      "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -193,16  193,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
    "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "11.070497693516351"
        "9.487729036781154"
       ]
      },
-     "execution_count": 5,
      "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -211,7  211,7 @@
     "# Задаём уровень значимости\n",
     "sign_level = 0.05\n",
     "# Критическое значение распределения chi2\n",
-    "chi2.ppf(q=1-sign_level, df=mod.exog.shape[1])"
     "chi2.ppf(q=1-sign_level, df=mod.df_model)"
    ]
   },
   {
@@ -238,16  238,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
    "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(75.45405182710722, 3.0150449532093895e-11)"
        "(75.45405182710691, 3.0150449532098e-11)"
       ]
      },
-     "execution_count": 6,
      "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -258,6  258,39 @@
     "lm, lm_pvalue"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Критическое значение $\\chi^2$-распределения"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
        "23.684791304840576"
       ]
      },
      "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Задаём уровень значимости\n",
     "sign_level = 0.05\n",
     "# Найдем степени свободы\n",
     "k = mod.df_model # число регрессоров\n",
     "df_white = 2 * k   k * (k-1) / 2\n",
     "# Критическое значение распределения chi2\n",
     "chi2.ppf(q=1-sign_level, df=df_white)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -288,7  321,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
    "version": "3.11.7"
   }
  },
  "nbformat": 4,

diff --git a/econometrica-1/jupyter-templates/diagnostic-het-template.ipynb b/econometrica-1/jupyter-templates/diagnostic-het-template.ipynb
@@ -95,7  95,7 @@
     "# Задаём уровень значимости\n",
     "sign_level = \n",
     "# Критическое значение распределения chi2\n",
-    "chi2.ppf(q=1-sign_level, df=mod.exog.shape[1])"
     "chi2.ppf(q=1-sign_level, df=mod.df_model)"
    ]
   },
   {
@@ -130,6  130,28 @@
     "lm, lm_pvalue"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "## Критическое значение $\\chi^2$-распределения"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Задаём уровень значимости\n",
     "sign_level = \n",
     "# Найдем степени свободы\n",
     "k = mod.df_model # число регрессоров\n",
     "df_white = 2 * k   k * (k-1) / 2\n",
     "# Критическое значение распределения chi2\n",
     "chi2.ppf(q=1-sign_level, df=df_white)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},