drawnuOR2 {bqror}

Samples scale factor \nu in the OR2 model

Description

This function samples \nu from a generalized inverse Gaussian (GIG) distribution in the OR2 model (ordinal quantile model with exactly 3 outcomes).

Usage

drawnuOR2(z, x, beta, sigma, tau2, theta, indexp)

Arguments

z

Gibbs draw of continuous latent values, a column vector of size (n x 1).

x

covariate matrix of size (n x k) including a column of ones.

beta

Gibbs draw of \beta, a column vector of size (k x 1).

sigma

\sigma, a scalar value.

tau2

2/(p(1-p)).

theta

(1-2p)/(p(1-p)).

indexp

index parameter of the GIG distribution which is equal to 0.5.

Details

This function samples \nu from a GIG distribution.

Value

\nu, a column vector of size (n x 1), sampled from a GIG distribution.

References

Rahman, M. A. (2016), '"Bayesian Quantile Regression for Ordinal Models."' Bayesian Analysis, 11(1), 1-24. DOI: 10.1214/15-BA939

Devroye, L. (2014). '"Random variate generation for the generalized inverse Gaussian distribution."' Statistics and Computing, 24(2): 239'-'246. DOI: 10.1007/s11222-012-9367-z

See Also

GIGrvg, Gibbs sampling, rgig

Examples

set.seed(101)
z <- c(21.01744, 33.54702, 33.09195, -3.677646,
 21.06553, 1.490476, 0.9618205, -6.743081, 21.02186, 0.6950479)
x <- matrix(c(
     1, -0.3010490, 0.8012506,
     1,  1.2764036, 0.4658184,
     1,  0.6595495, 1.7563655,
     1, -1.5024607, -0.8251381,
     1, -0.9733585, 0.2980610,
     1, -0.2869895, -1.0130274,
     1,  0.3101613, -1.6260663,
     1, -0.7736152, -1.4987616,
     1, 0.9961420, 1.2965952,
     1, -1.1372480, 1.7537353),
     nrow = 10, ncol = 3, byrow = TRUE)
beta <- c(-0.74441, 1.364846, 0.7159231)
sigma <- 3.749524
tau2 <- 10.6667
theta <- 2.6667
indexp <- 0.5
output <- drawnuOR2(z, x, beta, sigma, tau2, theta, indexp)

# output
#   5.177456 4.042261 8.950365
#   1.578122 6.968687 1.031987
#   4.13306 0.4681557 5.109653
#   0.1725333