spinar_est {spINAR} | R Documentation |
Semiparametric estimation of INAR models
Description
Semiparametric estimation of the autoregressive parameters and the innovation
distribution of INAR(p
) models, \code{p} \in \{1,2\}
. The
estimation is conducted by maximizing the conditional likelihood of the model.
Usage
spinar_est(x, p)
Arguments
x |
[ |
p |
[ |
Value
Vector containing the estimated coefficients \code{alpha}_1,...,\code{alpha}_p
and the estimated entries
of the pmf \code{pmf}_0, \code{pmf}_1
,... where \code{pmf}_i
represents the probability of
an innovation being equal to i
.
Examples
# generate data
dat1 <- spinar_sim(n = 200, p = 1, alpha = 0.5,
pmf = c(0.3, 0.3, 0.2, 0.1, 0.1))
dat2 <- spinar_sim(n = 200, p = 2, alpha = c(0.2, 0.3),
pmf = c(0.25, 0.2, 0.15, 0.1, 0.1, 0.1, 0.1))
# semiparametric estimation of INAR(1) model
spinar_est(x = dat1, p = 1)
# semiparametric estimation of INAR(2) model
spinar_est(x = dat2, p = 2)
[Package spINAR version 0.2.0 Index]