scDECO (version 0.1.1)

scdeco.cop: Copula dynamic correlation fitting function

Description

Copula dynamic correlation fitting function

Usage

scdeco.cop(
  y,
  x,
  marginals,
  w = NULL,
  n.mcmc = 10000,
  burn = 1000,
  thin = 1,
  offset1 = NULL,
  offset2 = NULL
)

Value

matrix with mcmc samples as rows and columns corresponding to the different parameters

Arguments

y

2-column matrix of observations

x

covariates

marginals

length-2 vector with strings of the two marginals

w

(optional)

n.mcmc

number of mcmc iterations to run

burn

how many of the mcmc iterations to burn

thin

how much to thin the mcmc iterations

offset1

(optional) offset for link(mu1)

offset2

(optional) offset for link(mu2)

Examples

n <- 1000
x.use = rnorm(n)
w.use = runif(n,-1,1)
eta1.use = c(-2.2, 0.7)
eta2.use = c(-2, 0.8)
beta1.use = c(1,0.5)
beta2.use = c(1,1)
alpha1.use = 7
alpha2.use = 3
tau.use = c(-0.2, .3)

marginals.use <- c("ZINB", "ZIGA")

y.use <- scdeco.sim.cop(marginals=marginals.use, x=x.use,
                    eta1.true=eta1.use, eta2.true=eta2.use,
                    beta1.true=beta1.use, beta2.true=beta2.use,
                    alpha1.true=alpha1.use, alpha2.true=alpha2.use,
                    tau.true=tau.use, w=w.use)
mcmc.out <- scdeco.cop(y=y.use, x=x.use, marginals=marginals.use, w=w.use,
                      n.mcmc=10, burn=0, thin=1) # n.mcmc=1000, burn=100, thin=5)

lowerupper <- t(apply(mcmc.out, 2, quantile, c(0.025, 0.5, 0.975)))
estmat <- cbind(lowerupper[,1],
                c(eta1.use, eta2.use, beta1.use, beta2.use, alpha1.use, alpha2.use, tau.use),
                lowerupper[,c(2,3)])
colnames(estmat) <- c("lower", "trueval", "estval", "upper")
estmat