cquad {cquad}

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)