vr.mle {gconsensus}

Finds the maximum likelihood estimate solution described by Vangel-Rukhin for the one way random effects model.

Description

This function finds the mle solution to the one way random effects model.

Usage

vr.mle(xi, si2, ni, labi=c(1:length(xi)), 
   max.iter=1000, tol=.Machine$double.eps^0.5, 
   init.mu=mean(xi), init.sigma2=var(xi), 
   trace=FALSE, alpha=0.05)

Arguments

xi

numeric vector, represents the mean values.

si2

numeric vector, represents the variances associated with a single measurement.

ni

integer vector, represents the number of observations associated with the reported mean values.

labi

vector, containing the associated labels of the participanting laboratories, source of the reported values (mean, variances, number of observations)

max.iter

integer, maximum number of iterations allowed.

tol

numeric, relative tolerance.

init.mu

numeric, initial consensus value.

init.sigma2

numeric, initial between variance.

trace

logic, indicates if traceable information must be shown during the execution.

alpha

numeric, significance level.

Value

mu

estimated consensus value by the method of maximum likelihood

u.mu

standard uncertainty estimation attached to the consensus value

kp

estimated expansion factor for the specified configuration options

Author(s)

Hugo Gasca-Aragon Maintainer: Hugo Gasca-Aragon <[e-mail]>

See Also

See also gconsensus