evaluate the probability of a beta parameter from the probability density function defined by old parameters
mukernel(y, x, z, betas.now, betas.old, gammas.ini, gl.ini, bpri, Bpri)
a matrix with the probability for the beta parameter from the probability density function defined by old parameters
object of class matrix, with the dependent variable
object of class matrix, with the variables for modelling the mean
object of class matrix, with the variables for modelling the variance
a vector with the beta parameters - new parameters - to evaluate in the old p.d.f
a vector with the beta parameters that define the old p.d.f
a vector with the gammas parameters that define the old p.d.f
a vector with the degrees of freedom parameter that define the old p.d.f
a vector with the initial values of beta
a matrix with the initial values of the variance of beta
Margarita Marin mmarinj@unal.edu.co, Edilberto Cepeda-Cuervo ecepedac@unal.edu.co
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).
1. Marin and Cepeda-Cuervo (_). A Bayesian regression model for the non-standardized t distribution with location, scale and degrees of freedom parameters. Unpublished
2. Cepeda-Cuervo E. (2001). Modelagem da variabilidade em modelos lineares generalizados. Unpublished Ph.D. tesis. Instituto de Matematicas. Universidade Federal do Rio do Janeiro.
3. Cepeda C., E. and Gamerman D. (2001). Bayesian Modeling of Variance Heterogeneity in Normal Regression Models. Brazilian Journal of Probability and Statistics. 14, 207-221