Covariance from standard deviation and correlation (covcorr)

版本 1.0.3 (1.5 KB) 作者: Gregory Pelletier

This MATLAB function converts standard deviation and the correlation matrix to a covariance matrix

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更新时间 2024/1/29

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This MATLAB function converts standard deviation and correlation to covariance

INPUTS:

psigma = vector of standard deviations for each of any number of variables or parameters

prho = correlation matrix of the correlations between each each variable or parameter

OUTPUTS:

pcov = covariance matrix between variables or parameters

EXAMPLE:

load hospital
X = [hospital.Weight hospital.BloodPressure];
% Find the correlation matrix for the variables X: 
prho = corrcoef(X)
% prho =
    % 1.0000    0.1558    0.2227
    % 0.1558    1.0000    0.5118
    % 0.2227    0.5118    1.0000
% Find the standard deviations of each variable X
psigma = std(X)
% psigma =
   % 26.5714    6.7128    6.9325
% Find the covariance matrix between variables X:
pcov = covcorr(psigma,prho)
% pcov =
  % 706.0404   27.7879   41.0202
   % 27.7879   45.0622   23.8194
   % 41.0202   23.8194   48.0590

引用格式

Gregory Pelletier (2024). Covariance from standard deviation and correlation (covcorr) (https://www.mathworks.com/matlabcentral/fileexchange/158046-covariance-from-standard-deviation-and-correlation-covcorr), MATLAB Central File Exchange. 检索来源 2024/8/27.