normalmixVcov: normalmixVcov

In hkasahar/normalregMix: normalregMix: An R Package for Normal Mixture Regression Models

Description

Computes the variance-covariance matrix of the MLE of m-component normal mixture.

Usage

normalmixVcov(y, coefficients, z = NULL, vcov.method = c("Hessian", "OPG"))

Arguments

y	n by 1 vector of data
coefficients	(alpha_1, ..., alpha_m, mu_1, ..., mu_m, sigma_1, ..., sigma_m, gam)
z	n by p matrix of regressor associated with gamma
vcov.method	Method used to compute the variance-covariance matrix, one of "Hessian" and "OPG". #' The default option is "Hessian". When method = "Hessian", the variance-covarince matrix is estimated by the Hessian using the formula given in Boldea and Magnus (2009). When method = "OPG", the outer product of gradients is used.

Value

The variance-covariance matrix of the MLE of m-component normal mixture given the data and coefficients.

References

Boldea, O. and Magnus, J. R. (2009) Maximum Likelihood Estimation of the Multivariate Normal Mixture Model, Journal of the American Statistical Association, 104, 1539–1549.

hkasahar/normalregMix documentation built on May 17, 2019, 4 p.m.