bootstrapreg

Version 1.0.0 (2.51 KB) by Shiyong Yu
A MATLAB program for bootstrapping a multivariate linear regression model
113 Downloads
Updated 18 May 2020

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Traditional regression analysis can only yield a point estimate, which is unable to assess the uncertainties in the model parameters. As the underlying distribution of the model parameters is unknown, we need to evaluate the predictive ability of our model somehow. Bootstrapping represents one of the efficient resampling algorithms that can generate large number of random numbers with frequency distribution assumed to mimic the actual distribution of the model parameters.

Bootstrapreg is a MATLAB program for bootstrapping a multivariate linear regression model y = beta0 + beta1*x1 + ... + betan*xn + error. The resampling residuals method was used to generate random numbers for updating the predictions reiteratively. This method by resampling the studentized residuals is better than the bootstrapping objects method, because any unused data in the original observations would undermine the accuracy of estimates of the model parameters.

Cite As

Yu, S.-Y., (2020). Bootstrapreg: A MATLAB program for bootstrapping a multivariate linear regression model. (https://www.mathworks.com/matlabcentral/fileexchange/), MATLAB Central File Exchange. Retrieved May 18, 2020.

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0