Computes an empirical fluctuation process according to a specified
method from the generalized fluctuation test framework. The test
utilises the function efp()
and its methods from
package ‘strucchange
’. Additionally, the function provides the option to
compute a multivariate chow test.
# S3 method for varest
stability(
x,
type = c("OLS-CUSUM", "Rec-CUSUM", "Rec-MOSUM", "OLS-MOSUM", "RE", "ME", "Score-CUSUM",
"Score-MOSUM", "fluctuation", "mv-chow-test"),
h = 0.15,
dynamic = FALSE,
rescale = TRUE,
...
)
A list with either class attribute ‘varstabil
’ or ‘chowpretest
’ holding the following elements
in case of class ‘varstabil
’:
A list with objects of class ‘efp
’; length is equal to the dimension of the VAR.
Character vector containing the names of the endogenous variables.
An integer of the VAR dimension.
In case of class ‘chowpretest
’ the list consists of the following elements:
A vector containing the calculated break point test statistics for all considered break points.
A vector containing the calculated sample split test statistics for all considered sample splits.
An integer sepcifying the first observation as possible break date.
An integer sepcifying the last observation as possible break date.
A list with objects of class ‘varest
’
Logical, if the break point test should be the benchmark for later analysis.
Object of class ‘varest
’; generated by VAR()
.
Specifies which type of fluctuation process will be computed, the default is ‘OLS-CUSUM
’.
For details see:efp
and chow.test
.
A numeric from interval (0,1) specifying the bandwidth. Determines the size of the data window
relative to sample size (for ‘MOSUM
’, ‘ME
’ and ‘mv-chow-test
’ only).
Logical. If ‘TRUE
’ the lagged observations are included as a regressor
(not if ‘type
’ is ‘mv-chow-test
’).
Logical. If ‘TRUE
’ the estimates will be standardized by the regressor matrix of the corresponding subsample;
if ‘FALSE
’ the whole regressor matrix will be used. (only if ‘type
’ is either ‘RE
’ or
‘E
’).
Ellipsis, is passed to strucchange::sctest()
, as default.
Bernhard Pfaff, Alexander Lange, Bernhard Dalheimer, Simone Maxand, Helmut Herwartz
For details, please refer to documentation efp
and chow.test
.
Zeileis, A., F. Leisch, K. Hornik and C. Kleiber (2002), strucchange: An R Package for Testing for Structural Change in Linear Regression
Models, Journal of Statistical Software, 7(2): 1-38, tools:::Rd_expr_doi("10.18637/jss.v007.i02")
and see the references provided in the reference section of efp
and chow.test
, too.
VAR
, plot
, efp
, chow.test
# \donttest{
data(Canada)
var.2c <- VAR(Canada, p = 2, type = "const")
var.2c.stabil <- stability(var.2c, type = "OLS-CUSUM")
var.2c.stabil
plot(var.2c.stabil)
data(USA)
v1 <- VAR(USA, p = 6)
x1 <- stability(v1, type = "mv-chow-test")
plot(x1)
# }
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