global.MNB: Global influence
In carrascojalmar/MNB: Diagnostic Tools for a Multivariate Negative Binomial Model

View source: R/global.R

global.MNB

R Documentation

Global influence

Description

It performers influence analysis by a global influence to evaluate the impact on the parameter estimates when we remove a particular observation.

Usage

global.MNB(formula, star, dataSet, plot = TRUE)

Arguments

`formula`	The structure matrix of covariates of dimension n x p (in models that include an intercept x should contain a column of ones).
`star`	Initial values for the parameters to be optimized over.
`dataSet`	data
`plot`	TRUE or FALSE. Indicates if a graph should be plotted.

Details

The function returns a list (L) with the generalized Cook distance, Likelihood displacement and index plot.

Value

L and graphics

Author(s)

Jalmar M F Carrasco <carrascojalmar@gmail.com>, Cristian M Villegas Lobos <master.villegas@gmail.com> and Lizandra C Fabio <lizandrafabio@gmail.com>

References

Fabio, L. C., Villegas, C., Carrasco, J. M. F., and de Castro, M. (2021). D Diagnostic tools for a multivariate negative binomial model for fitting correlated data with overdispersion. Communications in Statistics - Theory and Methods. https://doi.org/10.1080/03610926.2021.1939380.

Examples




data(seizures)
head(seizures)

star <-list(phi=1, beta0=1, beta1=1, beta2=1, beta3=1)
global.MNB(formula=Y ~ trt + period +
trt:period + offset(log(weeks)),star=star,dataSet=seizures,plot=FALSE)

carrascojalmar/MNB documentation built on May 15, 2022, 4:41 a.m.