tsdiagplot: Times series diagnostic plots for a structured set of ARIMA...

In HH: Statistical Analysis and Data Display: Heiberger and Holland

Times series diagnostic plots for a structured set of ARIMA models.

Description

Times series diagnostic plots for a structured set of ARIMA models.

Usage

tsdiagplot(x,
           p.max=2, q.max=p.max,
           model=c(p.max, 0, q.max), ## S-Plus
           order=c(p.max, 0, q.max), ## R
           lag.max=36, gof.lag=lag.max,
           armas=arma.loop(x, order=order,
               series=deparse(substitute(x)), ...),
           diags=diag.arma.loop(armas, x,
                                lag.max=lag.max,
                                gof.lag=gof.lag),
           ts.diag=rearrange.diag.arma.loop(diags),
           lag.units=ts.diag$tspar["frequency"],
           lag.lim=range(pretty(ts.diag$acf$lag))*lag.units,
           lag.x.at=pretty(ts.diag$acf$lag)*lag.units,
           lag.x.labels={tmp <- lag.x.at
                      tmp[as.integer(tmp)!=tmp] <- ""
                      tmp},
           lag.0=TRUE,
           main, lwd=0,
           ...)

acfplot(rdal, type="acf",
        main=paste("ACF of std.resid:", rdal$series,
                   "   model:",         rdal$model),
        lag.units=rdal$tspar["frequency"],
        lag.lim=range(pretty(rdal[[type]]$lag)*lag.units),
        lag.x.at=pretty(rdal[[type]]$lag)*lag.units,
        lag.x.labels={tmp <- lag.x.at
                      tmp[as.integer(tmp)!=tmp] <- ""
                      tmp},
        lag.0=TRUE,
        xlim=xlim.function(lag.lim/lag.units),
        ...)

aicsigplot(z, z.name=deparse(substitute(z)), series.name="ts",
           model=NULL,
           xlab="", ylab=z.name,
           main=paste(z.name,  series.name, model),
           layout=c(1,2), between=list(x=1,y=1), ...)

residplot(rdal,
          main=paste("std.resid:", rdal$series,
                     "   model:",  rdal$model),
          ...)

gofplot(rdal,
        main=paste("P-value for gof:", rdal$series,
                   "   model:",         rdal$model),
       lag.units=rdal$tspar["frequency"],
        lag.lim=range(pretty(rdal$gof$lag)*lag.units),
        lag.x.at=pretty(rdal$gof$lag)*lag.units,
        lag.x.labels={tmp <- lag.x.at
                      tmp[as.integer(tmp)!=tmp] <- ""
                      tmp},
        xlim=xlim.function(lag.lim/lag.units),
        pch=16, ...)

Arguments

x	Time series vector.
p.max, q.max	Maximum number of AR and MA arguments to use in the series of ARIMA models.
model	A valid S-Plus model for arima.mle.
order	A valid R order for arima. The additional argument seasonal may also be used.
lag.max	Maximum lag for the acf and pacf plots.
gof.lag	Maximum lag for the gof plots.
armas	An arma.loop object.
diags	An diag.arma.loop object.
ts.diag, rdal	A list constructed as a rearranged diag.arma.loop object.
lag.units	Units for time series, defaults to frequency(x)
lag.lim	scaling for xlim in acf and pacf plots.
lag.x.at, lag.x.labels	Location of ticks and labels for the acf and pacf plots.
lag.0	Logical. If TRUE, then plot the correlation (identically 1) at lag=0. If FALSE, do not plot the correlation at lag=0.
type	"acf" or "pacf"
z	A matrix constructed as the aic or sigma2 component of the sumamry of a arma.loop object.
z.name	"aic" or "sigma2"
series.name	Character string describing the time series.
xlab, ylab, layout, between, pch, xlim, main, lwd	Standard trellis arguments.
...	Additional arguments. tsdiagplot sends them to arima or arima.mle. acfplot, aicsigplot residplot, and gofplot send them to xyplot.

Value

tsdiagplot returns a "tsdiagplot" object which is a list of "trellis" objects. It is printed with its own print method.

The other functions return "trellis" objects.

Author(s)

Richard M. Heiberger ([e-mail])

References

"Displays for Direct Comparison of ARIMA Models" The American Statistician, May 2002, Vol. 56, No. 2, pp. 131-138. Richard M. Heiberger, Temple University, and Paulo Teles, Faculdade de Economia do Porto.

Heiberger, Richard M. and Holland, Burt (2015). Statistical Analysis and Data Display: An Intermediate Course with Examples in R. Second Edition. Springer-Verlag, New York. https://link.springer.com/book/10.1007/978-1-4939-2122-5

See Also

tsacfplots, arma.loop

Examples

data(tser.mystery.X)
X <- tser.mystery.X

X.dataplot <- tsacfplots(X, lwd=1, pch.seq=16, cex=.7)
X.dataplot

X.loop <- if.R(
               s=
               arma.loop(X, model=list(order=c(2,0,2)))
               ,r=
               arma.loop(X, order=c(2,0,2))
               )
X.dal <- diag.arma.loop(X.loop, x=X)
X.diag <- rearrange.diag.arma.loop(X.dal)
X.diagplot <- tsdiagplot(armas=X.loop, ts.diag=X.diag, lwd=1)
X.diagplot

X.loop
X.loop[["1","1"]]

HH documentation built on May 29, 2024, 6:24 a.m.