Internal function called by function zoib; Fits a fixed-effects beta regression to a response variable bounded within [0, 1].
fixed01(y, n, xmu.1, p.xmu, xsum.1, p.xsum, x0.1, p.x0, x1.1, p.x1, prior1, prec.int,
prec.DN, lambda.L1, lambda.L2, lambda.ARD, link, n.chain,inits, seed)Internal function. Returned values are used internally
A univariate response variable taking value from [0, 1].
Number of rows in the data set.
Design matrix associated with the fixed effects in the linear predictor of g(mean of the beta piece), where g() is link function.
Number of columns in xmu.1.
Design matrix associated with the fixed effects in linear predictor of log(dispersion parameter of the beta piece).
Number of columns in xsum.1.
Design matrix associated with fixed effects in the linear predictor of g(Pr(y=0)), where g() is link function
Number of columns in x0.1.
Design matrix associated with fixed effects in the linear predictor of g(Pr(y=1|y>0)), where g() is link function.
Number of columns in x1.1.
Internally generated variable (a vector of dimension 4). Prior choice for the regression coefficients in each of the 4 linear predictors of the 4 link functions.
The precision parameter in the prior distributions (diffuse normal) of the intercepts in the linear predictors.
The precision parmeter in the prior distributions of the regression coefficients in the linear predictors if the diffuse normal prior is chosen.
The scale parameter in the prior distributions of the regression coefficients in the linear predictors if the ARD prior is chosen.
The scale parameter in the prior distributions of the regression coefficients in the linear predictors if the L1-like prior is chosen.
The scale parameter in the prior distributions of the regression coefficients in the linear predictors if the L2-like prior is chosen.
Internally generated variable containing the information on the choice of link functions for the mean of the beta piece.
Number of chains for the MCMC sampling.
initial parameter for model parameters.
seeds for results reproducibility
Fang Liu (fang.liu.131@nd.edu)
See Also as zoib