test.linear {astsa} | R Documentation |
Produces a plot of the tail probabilities of a normalized bispectrum of a series under the assumption the model is a linear process with iid innovations.
test.linear(series, color = TRUE, detrend = FALSE)
series |
the time series (univariate only) |
color |
if FALSE, the graphic is produced in gray scale |
detrend |
if TRUE, the series is detrended first |
prob |
matrix of tail probabilities - returned invisibly |
The null hypothesis is that the data are from a linear process with i.i.d. innovations. Under the null hypothesis, the bispectrum is constant over all frequencies. Chi-squared test statistics are formed in blocks to measure departures from the null hypothesis and the corresponding p-values are displayed in a graphic and returned invisibly. Details are in Hinich, M. and Wolinsky, M. (2005). Normalizing bispectra. Journal of Statistical Planning and Inference, 130, 405–411.
D.S. Stoffer
You can find demonstrations of astsa capabilities at FUN WITH ASTSA.
The most recent version of the package can be found at https://github.com/nickpoison/astsa/.
In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.
The webpages for the texts are https://www.stat.pitt.edu/stoffer/tsa4/ and https://www.stat.pitt.edu/stoffer/tsda/.
## Not run: test.linear(nyse) # :( test.linear(soi) # :) ## End(Not run)