R: Conditional maximum likelihood estimation of the quadratic...
cquad_ext
R Documentation
Conditional maximum likelihood estimation of the quadratic exponential model for panel data
Description
Fit by conditional maximum likelihood the model for binary logitudinal data proposed by Bartolucci & Nigro (2010).
Usage
cquad_ext(id, yv, X = NULL, be = NULL, w = rep(1, n))
Arguments
id
list of the reference unit of each observation
yv
corresponding vector of response variables
X
corresponding matrix of covariates (optional)
be
intial vector of parameters (optional)
w
vector of weights (optional)
Value
formula
formula defining the model
lk
conditional log-likelihood value
coefficients
estimate of the regression parameters (including for the lag-response)
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")
References
Bartolucci, F. and Nigro, V. (2010), A dynamic model for binary panel data with unobserved heterogeneity admitting a root-n consistent conditional estimator. Econometrica, 78, pp. 719-733.
Examples
# example based on simulated data
data(data_sim)
data_sim = data_sim[1:500,] # to speed up the example, remove otherwise
id = data_sim$id; yv = data_sim$y; X = cbind(X1=data_sim$X1,X2=data_sim$X2)
# static model
out = cquad_ext(id,yv,X)
summary(out)