mixreg (version 0.0-2)

covmix: Calculate the covariance matrix of the parameter estimates for a mixture of regressions.

Description

Produces an estimate of the covariance matrix of the parameter estimates for a fitted mixture of linear regressions, by inverting the observed Fisher information matrix.

Usage

covmix(object, x, y)

Arguments

object

Object describing the fitted mixture of regressions, as returned by mixreg.

x

A matrix of predictors for each of the regression models in the mixture. It should NOT include an initial column of 1s. If there is only one predictor, x may be a vector.

y

The vector of responses for the regression models.

Value

• The estimated covariance matrix.

Details

If different variances are allowed amongst the components, the parameters are taken in the order beta.1, sigsq.1, lambda.1, ..., beta.K, sigsq.K for a K component model --- lambda.K is redundant and hence omitted. If equal variances are assumed, the parameters are taken in the order beta.1, lambda.1, ..., beta.K, sigsq.

In the foregoing beta refers to the linear coefficients, sigsq to the variance, and lambda to the mixing probability.

References

Turner, T. R. (2000) Estimating the rate of spread of a viral infection of potato plants via mixtures of regressions. Appl. Statist. vol. 49, Part 3, pp. 371 -- 384.

Louis, T. A. Finding the observed information matrix when using the EM algorithm, J. R. Statist. Soc. B, vol. 44, pp. 226 -- 233, 1982.

See Also

bootcomp, cband, mixreg, plot.cband, plot.mresid, qq.mix, resid.mix

Examples

#See \link{mixreg} for examples.