RegressionNoise

Revision as of 08:32, 4 May 2007 by Lchrisman (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)


RegressionNoise(Y,B,I,K,C)

When you have data, Y[I] and B[I,K], generated from an underlying model with unknown coefficients C[k] and S of the form:

Y = Sum( C*B, I) + Normal(0,S)

This function computes an estimate for S.

When using in conjunction with RegressionDist, it is most efficient to provide the optional parameter C to both routines, where C is the expected value of the regression coefficients, obtained from calling Regression(Y,B,I,K). Doing so avoids an unnecessary call to the builtin Regression function.

Library

Multivariate Distributions.ana

See Also

Comments


You are not allowed to post comments.