precision.mle.ncb.od {merror}R Documentation

Computes iterative approximation to mle precision estimates for nonconstant bias model using original data.

Description

This is an internal function that computes iterative approximation to mle precision estimates for nonconstant bias model using original data.

Usage

precision.mle.ncb.od(x, M = 20, beta.bars = beta.bar(x), jaech.errors = FALSE)

Arguments

x A matrix or numeric data.frame consisting of an n (no. of items) by N (no. of methods) matrix of measuremnts. N must be greater than 3 and n > N.
M Maximum no. of iterations for convergence.
beta.bars Estimates or hypothesized values for the betas.
jaech.errors TRUE replicates the minor error in Jaech's Fortran code to allow comparison with his examples.

Details

Provides iterative approximation to MLE precision estimates for NonConstant Bias model using Original Data. See Jaech, p. 185-186.

Value

sigma2 Estimated squared imprecisions (variances) for methods.
sigma.mu2 Estimated process variance.

Author(s)

Richard A. Bilonick rab@nauticom.net

References

Jaech, J. L. (1985) Statistical Analysis of Measurement Errors. New York: Wiley.

See Also

precision.grubbs.ncb.od,precision.grubbs.cb.pd


[Package merror version 1.0 Index]