get_SigmaG.glmm_nb_mod: Calculate Sigma and G matrices for Pseudo-likelihood Negative...

In ewynn610/corrRNASeq: Model Fitting for Correlated RNA-Seq Count Data

Calculate Sigma and G matrices for Pseudo-likelihood Negative Binomial Mixed Model

Description

Calculates the Sigma and G components described in Kenward and Roger (1997) while accounting for glmm_nb_mod object weights. Function is used in calculating Kenward-Roger degrees of freedom in functions from the pbkrtest-package such as KRmodcomp.

Usage

## S3 method for class 'glmm_nb_mod'
get_SigmaG(object, details = 0)

Arguments

object	A glmm_nb_mod model object from the glmm_nb_lmer function
details	If larger than 0 some timing details are printed.

Value

Sigma	The covariance matrix of Y
G	The G matrices that sum up to Sigma
n.ggamma	The number of G matrices (Called M in Kenward and Roger 1997)

Author(s)

Elizabeth Wynn and Camille Moore, underlying code drawn from code by pbkrtest-authors.

References

Kenward MG, Roger JH (1997). "Small Sample Inference for Fixed Effects from Restricted Maximum Likelihood." Biometrics, 53(3), 983. ISSN 0006341X. doi: 10.2307/2533558.

See Also

glmm_nb_mod, get_SigmaG, KRmodcomp

ewynn610/corrRNASeq documentation built on Sept. 29, 2023, 10:37 a.m.