gewekeParams: This function creates an object that summarizes the Geweke...

In COMIX: Coarsened Mixtures of Hierarchical Skew Kernels

This function creates an object that summarizes the Geweke convergence diagnostic.

Description

This function creates an object that summarizes the Geweke convergence diagnostic.

Usage

gewekeParams(
  res,
  params = c("w", "xi", "xi0", "psi", "G", "E", "eta"),
  frac1 = 0.1,
  frac2 = 0.5,
  probs = c(0.025, 0.975)
)

Arguments

res	An object of class COMIX or tidyChainCOMIX.
params	A character vector naming the parameters to compute the Geweke diagnostic for.
frac1	Double, fraction to use from beginning of chain.
frac2	Double, fraction to use from end of chain.
probs	A vector of 2 doubles, probabilities denoting the limits of a confidence interval for the convergence diagnostic.

Value

An gewekeParamsCOMIX object which is a named list, with a named element for each requested parameter. Each element is a data frame that includes the Geweke diagnostic and result of a stationarity test for the parameter.

Examples

library(COMIX)
# Number of observations for each sample (row) and cluster (column):
njk <- 
  matrix(
    c(
      150, 300,
      250, 200
    ),
    nrow = 2,
    byrow = TRUE
  )

# Dimension of data:
p <- 3

# Scale and skew parameters for first cluster:
Sigma1 <- matrix(0.5, nrow = p, ncol = p) + diag(0.5, nrow = p)
alpha1 <- rep(0, p)
alpha1[1] <- -5
# location parameter for first cluster in first sample:
xi11 <- rep(0, p)
# location parameter for first cluster in second sample (aligned with first):
xi21 <- rep(0, p)

# Scale and skew parameters for second cluster:
Sigma2 <- matrix(-1/3, nrow = p, ncol = p) + diag(1 + 1/3, nrow = p)
alpha2 <- rep(0, p)
alpha2[2] <- 5
# location parameter for second cluster in first sample:
xi12 <- rep(3, p)
# location parameter for second cluster in second sample (misaligned with first):
xi22 <- rep(4, p)

# Sample data:
set.seed(1)
Y <- 
  rbind(
    sn::rmsn(njk[1, 1], xi = xi11, Omega = Sigma1, alpha = alpha1),
    sn::rmsn(njk[1, 2], xi = xi12, Omega = Sigma2, alpha = alpha2),
    sn::rmsn(njk[2, 1], xi = xi21, Omega = Sigma1, alpha = alpha1),
    sn::rmsn(njk[2, 2], xi = xi22, Omega = Sigma2, alpha = alpha2)
  )

C <- c(rep(1, rowSums(njk)[1]), rep(2, rowSums(njk)[2]))

prior <- list(zeta = 1, K = 10)
pmc <- list(naprt = 5, nburn = 200, nsave = 200) # Reasonable usage
pmc <- list(naprt = 5, nburn = 2, nsave = 5) # Minimal usage for documentation
# Fit the model:
res <- comix(Y, C, pmc = pmc, prior = prior)

# Relabel to resolve potential label switching issues:
res_relab <- relabelChain(res)
effssz <- effectiveSampleSize(res_relab, "w")
# Or:
tidy_chain <- tidyChain(res_relab, "w")
gwk <- gewekeParams(tidy_chain, "w")
# (see vignette for a more detailed example)

COMIX documentation built on Nov. 23, 2022, 5:07 p.m.