| global.MNB {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)