RegressionNoise

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 by assuming that the sample noise is the same for each point in the data set.

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

• RegressionDist
• RegressionFitProb
• Regression