On 8/2/11 12:24 PM, dan wrote: > I have been using the OLSMultipleLinearRegression class successfully > for a while now, but I am having trouble in my current application. > > The code is very simple, and looks like this: > > OLSMultipleLinearRegression regression = new OLSMultipleLinearRegression(); > regression.setNoIntercept(true); > regression.newSampleData(ys, z_bars); > double [] new_eta = regression.estimateRegressionParameters(); > > When I run this code with my current data, all of the regression > coefficients come back as NaNs. > > In the input data, the z_bars are vectors that have been normalized to > sum to 1, and the ys are the logs of the "true" response variables (I > am trying to reproduce the results from a research paper, in which it > was claimed that logging the response variables made them more > normally distributed, resulting in a better fit). Is there something > wrong with my setup? It seems like, even if the logged data is not > very linear, that it should still be possible to obtain some OLS fit, > even if it is a poor one. Any help would be appreciated.
Are you sure there are no NaNs in your input data? Phil > > Thank you, > Dan > > --------------------------------------------------------------------- > To unsubscribe, e-mail: [email protected] > For additional commands, e-mail: [email protected] > > --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
