exdqlm (version 0.1.4)

exdqlmChecks: exDQLM Diagnostics

Description

The function computes the following for the model(s) provided: the posterior predictive loss criterion based off the check loss, the one-step-ahead distribution sequence and its KL divergence from normality. The function also plots the following: the qq-plot and ACF plot corresponding to the one-step-ahead distribution sequence, and a time series plot of the MAP standard forecast errors.

Usage

exdqlmChecks(
  y,
  m1,
  m2 = NULL,
  plot = TRUE,
  cols = c("grey", "grey"),
  ref = NULL
)

Value

A list containing the following is returned:

• `m1.uts` - The one-step-ahead distribution sequence of `m1`.

• `m1.KL` - The KL divergence of `m1.uts` and a standard normal.

• `m1.pplc` - The posterior predictive loss criterion of `m1` based off the check loss function.

• `m1.qq` - The ordered pairs of the qq-plot comparing `m1.uts` with a standard normal distribution.

• `m1.acf` - The autocorrelations of `m1.uts` by lag.

If `m2` is provided, analogous results for `m2` are also included in the list.

Arguments

y

A univariate time-series.

m1

An object of class "`exdqlm`".

m2

An optional additional object of class "`exdqlm`" to compare with `m1`.

plot

If `TRUE`, the following will be plotted for `m1` and `m2` (if provided): a qq-plot and ACF plot of the MAP one-step-ahead distribution sequence, and a time series plot of the standardized forecast errors.

cols

Color(s) used to plot diagnostics.

ref

Reference sample of size `length(y)` from a standard normal distribution used to compute the KL divergence.

Examples

# \donttest{
y = scIVTmag[1:100]
model = polytrendMod(1,mean(y),10)
M0 = exdqlmISVB(y,p0=0.85,model,df=c(0.95),dim.df = c(1),
                  gam.init=-3.5,sig.init=15)
check.out = exdqlmChecks(y,M0,plot=FALSE)
check.out$m1.KL
check.out$m1
# }