View source: R/exdqlmDiagnostics.R
| exdqlmDiagnostics | R Documentation |
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.
exdqlmDiagnostics(
m1,
m2 = NULL,
plot = TRUE,
cols = c("red", "blue"),
ref = NULL
)
m1 |
An object of class " |
m2 |
An optional additional object of class " |
plot |
If |
cols |
Color(s) used to plot diagnostics. |
ref |
Reference sample of size |
A object of class "exdqlmDiagnostics" containing the following:
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.
m1.rt - Run-time of the original model m1 in seconds.
m1.msfe - MAP standardized one-step-ahead forecast errors from the original model m1.
y - The original time-series used to fit m1.
If m2 is provided, analogous results for m2 are also included in the list.
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)
M0.diags = exdqlmDiagnostics(M0,plot=FALSE)
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