These are chat archives for thunder-project/thunder
anyone who runs the code ">> from thunder.factorization import PCA
data = tsc.loadBinary('data')
pca = PCA(k=3)
Regressionanalysis assumes a model y=βX where y represents an arbitrary record in your
Seriesand β is a row-vector of regression coefficients. So if the records in your
Seriesare of length T and you have S different regressors (each also of length T), then X should be a S-by-T matrix where each row contains the values of one of your regressors.
Seriesare vectors representing time, then each row of X will be the time-course of one of your stimuli/regressors.
BilinearRegressionModel, if I understand well the "betas" you get are based on the dimensionality of X2 ?