summary.lacm: Methods for `lacm` Objects

Description

Methods for fitted latent autoregressive count model objects of class "lacm"

Usage

# S3 method for lacm
summary(object, …)
# S3 method for lacm
print(x, digits = max(3L, getOption("digits") - 3L), …)
# S3 method for lacm
coef(object, …)
# S3 method for lacm
vcov(object, …) 
# S3 method for lacm
simulate(object, nsim = 1, seed = NULL, …)

Arguments

object, x

a fitted model object of class "lacm".

digits

the number of significant digits to use when printing.

nsim

number of response vectors to simulate. Defaults to 1.

seed

an object specifying if and how the random number generator should be initialized ('seeded'). See simulate.

...

additional optional arguments.

Value

The function summary.lacm returns an object of class "summary.lacm", a list of some components of the "lacm" object, plus

coefficients

a summary of the parameter estimates, standard errors, z-values and corresponding p-values.

clic

the composite likelihood information criterion.

The function simulate.lacm returns a list of simulated responses.

The function print returns the call and coefficients, coef returns the estimated coefficients and vcov the corresponding variance-covariance matrix.

References

Pedeli, X. and Varin, C. (2020). Pairwise likelihood estimation of latent autoregressive count models. Statistical Methods in Medical Research.10.1177/0962280220924068.

Examples

Run this code

# NOT RUN {
data("polio", package = "lacm")
## model components
trend <- 1:length(polio)
sin.term <- sin(2 * pi * trend / 12)
cos.term <- cos(2 * pi * trend / 12)
sin2.term <- sin(2 * pi * trend / 6)
cos2.term <- cos(2 * pi * trend / 6)
## fit model with pairwise likelihood of order 1
mod1 <- lacm(polio ~ I(trend * 10^(-3)) + sin.term + cos.term + sin2.term + cos2.term)
mod1
summary(mod1)
## refit with d = 3
mod3 <- update(mod1, d = 3)
summary(mod3)
# }