mukernel: the probability of a beta parameter from the probability...

In NegBinBetaBinreg: Negative Binomial and Beta Binomial Bayesian Regression Models

Description

evaluate the probability of a beta parameter from the probability density function defined by old parameters

Usage

mukernel(y, x, z, betas.now,betas.old,gammas.ini,bpri,Bpri,model,m,ni)

Arguments

y	object of class matrix or vector, with the dependent variable.
x	object of class matrix, with the variables for modelling the mean.
z	object of class matrix, with the variables for modelling the shape, variance or dispersion.
betas.now	a vector with the beta parameter, new parameter, to evaluate in the old p.d.f
betas.old	a vector with the beta that define the old p.d.f
gammas.ini	a vector with the gamma that define the old p.d.f
bpri	a vector with the prior values of beta.
Bpri	a matrix with the prior values of the variance of beta.
model	it indicates the model that will be used. By default, is the Beta Binomial model (BB), but it could also be the Negative Binomial with mean and shape (NB1) or the Negative Binomial with mean and variance (NB2).
m	It is positive integer that In the Beta Binomial model indicates the number of trials. By default, is the number of data
ni	It is a vector of positive integer that In the Beta Binomial model indicates the number of trials to each individual. By default, is a vector of m

Details

Evaluate the probability of a beta parameter from the probability density function defined by old parameters, according with the model proposed by Cepeda(2001) and Cepeda and Gamerman(2005).

Value

value

a matrix with the probability for the beta parameter from the probability density function defined by old parameters

Author(s)

Edilberto Cepeda-Cuervo [e-mail], Maria Victoria Cifuentes-Amado [e-mail], Margarita Marin [e-mail]

References

1. Cepeda C. E. (2001). Modelagem da variabilidade em modelos lineares generalizados. Unpublished Ph.D. tesis. Instituto de Matematicas. Universidade Federal do Rio do Janeiro. //http://www.docentes.unal.edu.co/ecepedac/docs/MODELAGEM20DA20VARIABILIDADE.pdf. http://www.bdigital.unal.edu.co/9394/. 2.Cepeda, E. C. and Gamerman D. (2005). Bayesian Methodology for modeling parameters in the two-parameter exponential family. Estadistica 57, 93 105. // 3.Cepeda, E. and Garrido, L. (2011). Bayesian beta regression models: joint mean and precision modeling. Universidad Nacional // 4.Cepeda, E. and Migon, H. and Garrido, L. and Achcar, J. (2012) Generalized Linear models with random effects in the two parameter exponential family. Journal of Statistical Computation and Simulation. 1, 1 13. // 5.Cepeda-Cuervo, E. and Cifuentes-Amado, V. (2016) Double generalized beta-binomial and negative binomial regression. To appear.

NegBinBetaBinreg documentation built on May 2, 2019, 10:52 a.m.