sctest.formula: Structural Change Tests

Description

Performs tests for structural change.

Usage

## S3 method for class 'formula':
sctest(formula, type = <>, h = 0.15,
    alt.boundary = FALSE, functional = c("max", "range",
    "maxL2", "meanL2"), from = 0.15, to = NULL, point = 0.5,
    asymptotic = FALSE, data, ...)

Arguments

formula

a formula describing the model to be tested.

type

a character string specifying the structural change test that ist to be performed. Besides the tests types described in efp and sctest.Fstats. Th

numeric from interval (0,1) specifying the bandwidth. Determins the size of the data window relative to sample size (for MOSUM and ME tests only).

alt.boundary

logical. If set to TRUE alternative boundaries (instead of the standard linear boundaries) will be used (for CUSUM processes only).

functional

indicates which functional should be used to aggregate the empirical fluctuation processes to a test statistic.

from, to

numerics. If from is smaller than 1 they are interpreted as percentages of data and by default to is taken to be the 1 - from. F statistics will be calculated for the observations (n*from):(n*to)

point

parameter of the Chow test for the potential change point. Interpreted analogous to the from parameter. By default taken to be floor(n*0.5) if n is the number of observations in the model.

asymptotic

logical. If TRUE the asymptotic (chi-square) distribution instead of the exact (F) distribution will be used to compute the p value (for Chow test only).

data

an optional data frame containing the variables in the model. By default the variables are taken from the environment which sctest is called from.

...

further arguments passed to efp or Fstats.

Value

an object of class "htest" containing:
- statistic
{the test statistic}
p.valuethe corresponding p value
methoda character string with the method used
data.namea character string with the data name

Details

sctest.formula is mainly a wrapper for sctest.efp and sctest.Fstats as it fits an empirical fluctuation process first or computes the F statistics respectively and subsequently performs the corresponding test. The Chow test and the Nyblom-Hansen test are available explicitely here.

Examples

Run this code

## Load dataset "nhtemp" with average yearly temperatures in New Haven
data(nhtemp)
## plot the data
plot(nhtemp)

## test the model null hypothesis that the average temperature remains
## constant over the years with the Standard CUSUM test
sctest(nhtemp ~ 1)
## with the Chow test (under the alternative that there is a change 1941)
sctest(nhtemp ~ 1, type = "Chow", point = c(1941,1))