Commit b4204f8b by Johannes Pfeifer Committed by Stéphane Adjemian (Charybdis)

Make sure that mean and covariance of data are correctly computed with only one observation

```Need to always compute mean along first dimension

(cherry picked from commit 2d371b1997f5fa07fcbbf47e5923d7817d07c6b9)```
parent 0d11246c
 ... ... @@ -267,7 +267,7 @@ else end % Compute the empirical mean of the observed variables. DatasetInfo.descriptive.mean = nanmean(DynareDataset.data); DatasetInfo.descriptive.mean = nanmean(DynareDataset.data,1); % Compute the empirical covariance matrix of the observed variables. DatasetInfo.descriptive.covariance = nancovariance(DynareDataset.data); ... ...
 ... ... @@ -51,7 +51,7 @@ function CovarianceMatrix = nancovariance(data) CovarianceMatrix = zeros(size(data,2)); if isanynan(data) data = bsxfun(@minus,data,nanmean(data)); data = bsxfun(@minus,data,nanmean(data,1)); for i=1:size(data,2) for j=i:size(data,2) CovarianceMatrix(i,j) = nanmean(data(:,i).*data(:,j)); ... ... @@ -61,7 +61,7 @@ if isanynan(data) end end else data = bsxfun(@minus,data,mean(data)); data = bsxfun(@minus,data,mean(data,1)); CovarianceMatrix = (transpose(data)*data)/size(data,1); end ... ...
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!