gets (version 0.29)

dlogitxSim: Simulate from a dynamic logit-x model

Description

Simulate from a dynamic Autoregressive (AR) logit model with covariates ('X'). This model is essentially a logit-version of the model of Kauppi and Saikkonen (2008).

Usage

dlogitxSim(n, intercept = 0, ar = NULL, xreg = NULL, verbose = FALSE, 
    as.zoo = TRUE)

Arguments

n

integer, the number of observations to generate

intercept

numeric, the value of the intercept in the logit specification

ar

NULL or a numeric vector with the autoregressive parameters

xreg

NULL or numeric vector with the values of the X-term

verbose

logical. If FALSE, then only the binary process (a vector) is returned. If TRUE, then a matrix with all the simulated information is returned (binary process, probabilities, etc.)

as.zoo

logical. If TRUE, then the returned object - a vector or matrix - will be of class zoo

Value

A vector or matrix, depending on whether verbose is FALSE or TRUE, of class zoo, depending on whether as.zoo is TRUE or FALSE

Details

No details, for the moment.

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

dlogitx

Examples

# NOT RUN {
##simulate from ar(1):
set.seed(123) #for reproducibility
y <- dlogitxSim(100, ar=0.3)

##more output (value, probability, logit):
set.seed(123) #for reproducibility
y <- dlogitxSim(100, ar=0.3, verbose=TRUE)

# }