Internal function to be called by function zoib. Jointly models multiple [0,1]-bounded variables with inflation at both 0 and 1 when there is a single random variable in the linear predictors of the link functions
joint.1z01(y, n, q, xmu.1, p.xmu, xsum.1, p.xsum, x1.1, p.x1, x0.1, p.x0, inflate0,
inflate1, rid, EUID, nEU, prior1, prior2, prior.beta, prior.Sigma, prec.int,prec.DN,
lambda.L1, lambda.L2, lambda.ARD, scale.unif, scale.halft, link, n.chain,inits,seed)Internal function. Returned values are used internally
>=2 response variables taking value from [0, 1].
Number of rows in the data set.
Number of response variables.
Design matrix associated with the fixed effects in the linear predictor of g(mean of the beta piece), where g() is a link function.
Number of columns in xmu.1.
Design matrix associated with fixed effects in linear predictor of the log(dispersion parameter of the beta piece).
Number of columns in xsum.1.
Design matrix associated with the fixed effects in the linear predictor of g(Pr(y=1|y>0)), where g() is a link function.
Number of columns in x1.1.
Design matrix associated with the fixed effects in the linear predictor of g(Pr(y=0)), where g() is a link function.
Number of columns in x0.1.
Logical vector containing the information on which response variables have inflation at 0.
Logical vector variable containing the information on which response variables have inflation at 1.
Data vector containing the information on which linear predictors have a random component.
Listing of experimental unit ID for each row of the data set.
Number of experimental units
A vector containing the prior choice for the regression coefficients in each of the 4 linear predictors of the 4 link functions.
A matrix of dimension containing the prior choice for the covariance structure of the random variables.
Prior choice for the regression coefficients in each of the 4 link functions (a vector of dim = 4).
Prior choice for the Covariance structure of the random variables.
The precision in the prior distributions (diffuse normal) of the intercepts in the linear predictors.
The precision in the prior distributions of the regression coefficients in the linear predictors if 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.
The upper bound of the uniform distribution for the standard deviation of each random variable
The scale parameter of the half-Cauchy distribution for the standard deviation of each random variable
A matrix containing the information on the choice of link function 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