sluacf: Computes autocorrelations (ACF) for a time series

In statmanrobin/Stat2Data: Datasets for Stat2

Description

This function computes autocorrelations for various lags of a time series.

Usage

sluacf(series, lags = 1, maxlag = NULL, ndiff = 0, sdiff = 0)

Arguments

series	a time series object
lags	a multiplier for the lag. For example, use lag=12 for monthly data.
maxlag	maximum number of lags to compute
ndiff	number of regular differences to take before finding the ACF
sdiff	number of seasonal differences (with seasonal period specified by lags)

Details

This is is a wrapper for the acf function which allows for specifying regular (ndiff) and seasonal (sdiff) differences. The lags parameter specifies the seasonal lag and adjusts the default lags in the returned acf object to go 1, 2, ..., rather than showing fractional lags (for example, 1/12, 2/12, ... for monthly data). The lag 0 autocorrelation is set to NA (rather than 1) so that it won;t show when acf is plotted.

Value

An object of class "acf"

Examples

data(SeaIce)
ExtentY=ts(SeaIce$Extent,start=1979)
sluacf(ExtentY)
sluacf(ExtentY, maxlag=8,ndiff=1)

data(Inflation)
CPIts=ts(Inflation$CPI,start=c(2009,1),frequency=12)
CPIacf=sluacf(CPIts,maxlag=36,lags=12)
plot(CPIacf,lwd=2,ci.type="ma",xlim=c(1,36),xaxp=c(0,36,6),main="")

statmanrobin/Stat2Data documentation built on May 24, 2019, 1:34 a.m.