Python中的MatLab回归

如何解决Python中的MatLab回归

我有一些关于使用蒙特卡罗模拟和 OLS 回归来估计一些系数的 Matlab 代码。如何在 Python 中做到这一点？

Define the true DGP parameters and distributions
% Set the parameters in the model
b1 = 5;
b2 = -2;
% The variance of the error term
sigma2 = 2;
% The sample length. We will play with three different sample sizes and see how this affects the results 
N = [100 500 1000];
% The number of simulations
S = 1000;
Generate x data
% Generate the x values as draws from the multivariate normal distributions
% This is the correlation structure between the x's
Sigma   = [0.7 0.4;
            0.4 0.3];
% Simple way of drawing random numbers from the multivariate normal distribution        
x       = chol(Sigma)'*randn(2,max(N));    
% Make the x1 and x2 variables
x1      = x(1,:)';
x2      = x(2,:)';
Monte Carlo simulation 1
y = b1*x1 + e is the true model 
We will Now simulate data from this model and then use OLS to estimate two versions of the model: 
y = b1mc*x1 + e and 
y = b1mc_2*x1 + b2*x2 + e 
% Always good practive to allocate empty output before loops
b1mc    = nan(S,numel(N));
b1mc_2  = nan(S,numel(N));
% Simple counter to use when allocating results into b1mc below
cnt  = 1;
for n = N % Loop over the different sample sizes N
    for s = 1 : S
        % generate random errors
        u = randn(n,1)*sqrt(sigma2);    
        % simulate the process
        y = b1*x1(1:n) + u;           
        % Estimate coefficients by OLS (easy in Matlab) and save
        b1mc(s,cnt)     = x1(1:n)\y; 
        tmp             = [x1(1:n) x2(1:n)]\y;                                
        b1mc_2(s,cnt)   = tmp(1); % Only save the first parameter
    end
    cnt = cnt + 1;
end

解决方法

有一些方法可以在 python 中使用 MATLAB 代码！！...检查下面的链接

[检查这个] A tool to convert MATLAB code to Python