summary.lacm {lacm}

Methods for lacm Objects

Description

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

Usage

## S3 method for class 'lacm'
summary(object, ...)

## S3 method for class 'lacm'
print(x, digits = max(3L, getOption("digits") - 3L), ...)

## S3 method for class 'lacm'
coef(object, ...)

## S3 method for class 'lacm'
vcov(object, ...) 

## S3 method for class '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.

Author(s)

Xanthi Pedeli and Cristiano Varin.

References

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

See Also

CLIC.

Examples

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)