cquad: Interface for functions fitting different versions of cquad

In cquad: Conditional Maximum Likelihood for Quadratic Exponential Models for Binary Panel Data

Interface for functions fitting different versions of cquad

Description

Fit by conditional maximum likelihood each of the models in cquad package.

Usage

cquad(formula, data, index = NULL, model = c("basic","equal","extended","pseudo"),
             w = rep(1, n), dyn = FALSE, Ttol=10)

Arguments

formula	formula with the same syntax as in plm package
data	data.frame or pdata.frame
index	to denote panel structure as in plm package
model	type of model = "basic", "equal", "extended", "pseudo"
w	vector of weights (optional)
dyn	TRUE if in the dynamic version; FALSE for the static version (by default)
Ttol	Threshold individual observations that activates the recursive algorithm (default=10)

Value

formula	formula defining the model
lk	conditional log-likelihood value
coefficients	estimate of the regression parameters
vcov	asymptotic variance-covariance matrix for the parameter estimates
scv	matrix of individual scores
J	Hessian of the log-likelihood function
se	standard errors
ser	robust standard errors
Tv	number of time occasions for each unit

Author(s)

Francesco Bartolucci (University of Perugia), Claudia Pigini (University of Ancona "Politecnica delle Marche"), Francesco Valentini (University of Ancona "Politecnica delle Marche")

Examples

# example based on simulated data
data(data_sim)
data_sim = data_sim[1:500,]   # to speed up the example, remove otherwise
# basic (static) model
out1 = cquad(y~X1+X2,data_sim)
summary(out1)
# basic (dynamic) model
out2 = cquad(y~X1+X2,data_sim,dyn=TRUE)
summary(out2)
# equal model
out3 = cquad(y~X1+X2,data_sim,model="equal")
summary(out3)
# extended model
out4 = cquad(y~X1+X2,data_sim,model="extended")
summary(out4)
# psuedo CML for dynamic model
out5 = cquad(y~X1+X2,data_sim,model="pseudo")
summary(out5)

cquad documentation built on March 7, 2023, 6:15 p.m.