which.hypothesis.partest: Returns the preferred hypothesis when testing for partial...

In partialAR: Partial Autoregression

Description

Returns the preferred hypothesis when testing for partial autoregression

Usage

which.hypothesis.partest(AT)

Arguments

AT	An object of class "partest" returned from a previous call to test.par.

Details

Based upon the critical value alpha used in the call to test.par, and based upon the statistics computed by test.par, selects a preferred explanatory hypothesis for the data and returns a string representing the chosen hypothesis.

Value

One of the following strings:

"RW"	The preferred hypothesis is a pure random walk
"AR1"	The preferred hypothesis is a pure AR(1) series
"PAR"	The preferred hypothesis is a partially autoregressive series
"RRW"	The preferred hypothesis is a random walk with t-distributed innovations
"RAR1"	The preferred hypothesis is a pure AR(1) series with t-distributed innovations
"RPAR"	The preferred hypothesis is a partially autoregressive model with t-distributed innovations

Author(s)

Matthew Clegg [e-mail]

References

Matthew Clegg (2015): Modeling Time Series with Both Permanent and Transient Components using the Partially Autoregressive Model. Available at SSRN: http://ssrn.com/abstract=2556957.

See Also

fit.par test.par

Examples

set.seed(1)
which.hypothesis.partest(test.par(rpar(1000, 0, 1, 0)))  # -> "AR1"
which.hypothesis.partest(test.par(rpar(1000, 0, 0, 1)))  # -> "RW"
which.hypothesis.partest(test.par(rpar(1000, 0, 1, 1)))  # -> "PAR"

which.hypothesis.partest(test.par(rpar(1000, 0, 1, 0), robust=TRUE))   # -> "RAR1"
which.hypothesis.partest(test.par(rpar(1000, 0, 0, 1), robust=TRUE))   # -> "RRW"
which.hypothesis.partest(test.par(rpar(1000, 0.5, 1, 1), robust=TRUE)) # -> "RPAR"

partialAR documentation built on April 14, 2020, 6:05 p.m.