NegBinBetaBinreg (version 1.0)

gammakernel: the probability of a gamma parameter from the probability density funcion defined by old parameters

Description

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

Usage

gammakernel(y, x, z,betas.ini,gammas.now,gammas.old,gpri,Gpri,model,m,ni)

Arguments

y

object of class matrix, 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 variance

betas.ini

a vector with the beta that define the old p.d.f

gammas.now

a vector with the gamma parameter - new parameters - to evaluate in the old p.d.f

gammas.old

a vector with the gamma that define the old p.d.f

gpri

a vector with the initial values of gamma

Gpri

a matrix with the initial values of the variance of gamma

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

Value

Details

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

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 Unpublished Ph.D. tesis.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.