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mikbuch/ols_linear_multiple_regression.c

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ols_linear_multiple_regression.c
#include <stdio.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_math.h>
#include <gsl/gsl_multifit.h>
/* Interest rate */
double r[] = { 2.75, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.25,
2.25, 2.25, 2,2, 2, 1.75, 1.75, 1.75, 1.75,
1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75 };
/* Unemployment rate */
double u[] = { 5.3, 5.3, 5.3, 5.3, 5.4, 5.6, 5.5, 5.5,
5.5, 5.6, 5.7, 5.9, 6, 5.9, 5.8, 6.1,
6.2, 6.1, 6.1, 6.1, 5.9, 6.2, 6.2, 6.1 };
/* Stock index price */
double s[] = { 1464, 1394, 1357, 1293, 1256, 1254, 1234,
1195, 1159, 1167, 1130, 1075, 1047, 965, 943,
958, 971, 949, 884, 866, 876, 822, 704, 719 };
int main()
{
int n = sizeof(r)/sizeof(double);
gsl_matrix *X = gsl_matrix_calloc(n, 3);
gsl_vector *Y = gsl_vector_alloc(n);
gsl_vector *beta = gsl_vector_alloc(3);
for (int i = 0; i < n; i++) {
gsl_vector_set(Y, i, s[i]);
gsl_matrix_set(X, i, 0, 1);
gsl_matrix_set(X, i, 1, r[i]);
gsl_matrix_set(X, i, 2, u[i]);
}
double chisq;
gsl_matrix *cov = gsl_matrix_alloc(3, 3);
gsl_multifit_linear_workspace * wspc = gsl_multifit_linear_alloc(n, 3);
gsl_multifit_linear(X, Y, beta, cov, &chisq, wspc);
printf("Beta:");
for (int i = 0; i < 3; i++)
printf(" %g", gsl_vector_get(beta, i));
printf("\n");
gsl_matrix_free(X);
gsl_matrix_free(cov);
gsl_vector_free(Y);
gsl_vector_free(beta);
gsl_multifit_linear_free(wspc);
}
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ols_linear_multiple_regression.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Example code from: https://rosettacode.org/wiki/Multiple_regression#Python\n",
"\n",
"Data from: https://datatofish.com/multiple-linear-regression-python/"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"matrix([[1464, 1394, 1357, 1293, 1256, 1254, 1234, 1195, 1159, 1167,\n",
" 1130, 1075, 1047, 965, 943, 958, 971, 949, 884, 866,\n",
" 876, 822, 704, 719]])"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"interest_rate = [2.75, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.25,\n",
" 2.25, 2.25, 2,2, 2, 1.75, 1.75, 1.75, 1.75,\n",
" 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75]\n",
"\n",
"unemployment_rate = [5.3, 5.3, 5.3, 5.3, 5.4, 5.6, 5.5, 5.5,\n",
" 5.5, 5.6, 5.7, 5.9, 6, 5.9, 5.8, 6.1,\n",
" 6.2, 6.1, 6.1, 6.1, 5.9, 6.2, 6.2, 6.1]\n",
"\n",
"stock_index_price = [1464, 1394, 1357, 1293, 1256, 1254, 1234,\n",
" 1195, 1159, 1167, 1130, 1075, 1047, 965, 943,\n",
" 958, 971, 949, 884, 866, 876, 822, 704, 719]\n",
"\n",
"y = np.mat(stock_index_price)\n",
"y"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The observed trend"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(np.arange(len(stock_index_price)),\n",
" stock_index_price)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[-99.46431881 564.20389249]\n"
]
}
],
"source": [
"X = np.mat(interest_rate**np.arange(2)[:, None])\n",
"\n",
"betas = np.asarray(y * X.T * (X*X.T).I)[0]\n",
"print(betas)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([1452.09638554, 1311.04541242, 1311.04541242, 1311.04541242,\n",
" 1311.04541242, 1311.04541242, 1311.04541242, 1169.9944393 ,\n",
" 1169.9944393 , 1169.9944393 , 1028.94346617, 1028.94346617,\n",
" 1028.94346617, 887.89249305, 887.89249305, 887.89249305,\n",
" 887.89249305, 887.89249305, 887.89249305, 887.89249305,\n",
" 887.89249305, 887.89249305, 887.89249305, 887.89249305])"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.asarray(interest_rate)*betas[1]+betas[0]"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(np.arange(len(interest_rate)),\n",
" interest_rate)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(interest_rate, stock_index_price)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(np.arange(len(stock_index_price)),\n",
" stock_index_price)\n",
"plt.scatter(np.arange(len(stock_index_price)),\n",
" np.asarray(interest_rate)*betas[1]+betas[0])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"matrix([[1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ,\n",
" 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ,\n",
" 1. , 1. , 1. , 1. ],\n",
" [2.75, 2.5 , 2.5 , 2.5 , 2.5 , 2.5 , 2.5 , 2.25, 2.25, 2.25,\n",
" 2. , 2. , 2. , 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75,\n",
" 1.75, 1.75, 1.75, 1.75]])"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[4471.33932136 -588.96207585]\n"
]
}
],
"source": [
"X = np.mat(unemployment_rate**np.arange(2)[:, None])\n",
" \n",
"betas = np.asarray(y * X.T * (X*X.T).I)[0]\n",
"print(betas)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(np.arange(len(unemployment_rate)),\n",
" unemployment_rate)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(unemployment_rate, stock_index_price)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(np.arange(len(stock_index_price)),\n",
" stock_index_price)\n",
"plt.scatter(np.arange(len(stock_index_price)),\n",
" np.asarray(unemployment_rate)*betas[1]+betas[0])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"matrix([[1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ,\n",
" 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ],\n",
" [5.3, 5.3, 5.3, 5.3, 5.4, 5.6, 5.5, 5.5, 5.5, 5.6, 5.7, 5.9, 6. ,\n",
" 5.9, 5.8, 6.1, 6.2, 6.1, 6.1, 6.1, 5.9, 6.2, 6.2, 6.1]])"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[1798.40397763 345.54008701 -250.14657137]\n"
]
}
],
"source": [
"X = np.asmatrix(np.array([np.ones(len(stock_index_price)),\n",
" interest_rate,\n",
" unemployment_rate]))\n",
"\n",
"betas = np.asarray(y * X.T * (X*X.T).I)[0]\n",
"print(betas)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(interest_rate, stock_index_price)\n",
"plt.scatter(unemployment_rate, stock_index_price)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.scatter(np.arange(len(stock_index_price)),\n",
" stock_index_price)\n",
"\n",
"plt.scatter(np.arange(len(stock_index_price)),\n",
" (np.asarray(interest_rate)*betas[1] + np.asarray(unemployment_rate)*betas[2] + betas[0]))\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"matrix([[1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ,\n",
" 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. , 1. ,\n",
" 1. , 1. , 1. , 1. ],\n",
" [2.75, 2.5 , 2.5 , 2.5 , 2.5 , 2.5 , 2.5 , 2.25, 2.25, 2.25,\n",
" 2. , 2. , 2. , 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75,\n",
" 1.75, 1.75, 1.75, 1.75],\n",
" [5.3 , 5.3 , 5.3 , 5.3 , 5.4 , 5.6 , 5.5 , 5.5 , 5.5 , 5.6 ,\n",
" 5.7 , 5.9 , 6. , 5.9 , 5.8 , 6.1 , 6.2 , 6.1 , 6.1 , 6.1 ,\n",
" 5.9 , 6.2 , 6.2 , 6.1 ]])"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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