| envelope.MNB {MNB} | R Documentation |
Simulation envelope
Description
Simulated envelopes in normal probability plots
Usage
envelope.MNB(star, formula, dataSet, n.r, nsim, plot = TRUE)
Arguments
star |
Initial values for the parameters to be optimized over. |
formula |
The structure matrix of covariates of dimension n x p (in models that include an intercept x should contain a column of ones). |
dataSet |
data |
n.r |
Indicator which residual type graphics. 1 - weighted, 2 - Standardized weighted, 3 - Pearson, 4 - Standardized Pearson, 5 - standardized deviance component residuals and 6 - randomized quantile residuals. |
nsim |
Number of Monte Carlo replicates. |
plot |
TRUE or FALSE. Indicates if a graph should be plotted. |
Details
Atkinson (1985), suggests the use of simulated envelopes in normal probability plots to facilitate the goodness of fit.
Value
L, residuals and simulation envelopes in normal probability plots
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
Atkinson A.C. (1985). Plots, Transformations and Regression: An Introduction to Graphical Methods of Diagnostic Regression Analysis. Oxford University Press, New York.
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)
envelope.MNB(formula=Y ~ trt + period + trt:period +
offset(weeks),star=star,nsim=21,n.r=6,
dataSet=seizures,plot=FALSE)
data(alzheimer)
head(alzheimer)
star <- list(phi=10,beta1=2, beta2=0.2)
envelope.MNB(formula=Y ~ trat, star=star, nsim=21, n.r=6,
dataSet = alzheimer,plot=FALSE)