gets.logitx {gets} | R Documentation |
General-to-Specific (GETS) Modelling of objects of class 'logitx'
Description
General-to-Specific (GETS) Modelling of a dynamic Autoregressive (AR) logit model with covariates ('X') of class 'dlogitx'.
Usage
## S3 method for class 'logitx'
gets(x, t.pval = 0.05, wald.pval = t.pval, do.pet = TRUE,
user.diagnostics = NULL, keep = NULL, include.gum = FALSE,
include.1cut = TRUE, include.empty = FALSE, max.paths = NULL,
turbo = TRUE, print.searchinfo = TRUE, plot = NULL, alarm = FALSE,
...)
Arguments
x |
an object of class 'logitx', see |
t.pval |
numeric value between 0 and 1. The significance level used for the two-sided regressor significance t-tests |
wald.pval |
numeric value between 0 and 1. The significance level used for the Parsimonious Encompassing Tests (PETs). By default, it is the same as |
do.pet |
|
user.diagnostics |
|
keep |
|
include.gum |
|
include.1cut |
|
include.empty |
|
max.paths |
|
turbo |
|
print.searchinfo |
|
plot |
|
alarm |
|
... |
further arguments passed to or from other methods |
Details
The model of class 'logitx' is a dynamic Autoregressive (AR) logit model with (optional) covariates ('X') proposed by Kauppi and Saikkonen (2008). Internally, gets.logitx
undertakes the General-to-Specific (GETS) modelling with the getsFun
function, see Sucarrat (2020).
Author(s)
Genaro Sucarrat, http://www.sucarrat.net/
References
Heikki Kauppi and Penti Saikkonen (2008): 'Predicting U.S. Recessions with Dynamic Binary Response Models'. The Review of Economic Statistics 90, pp. 777-791
See Also
logitx
, logitxSim
, coef.logitx
, getsFun
Examples
##simulate from ar(1), create covariates:
set.seed(123) #for reproducibility
y <- logitxSim(100, ar=0.3)
x <- matrix(rnorm(5*100), 100, 5)
##estimate model:
mymod <- logitx(y, ar=1:4, xreg=x)
##do gets modelling:
gets(mymod)