R: Conditional maximum likelihood estimation for the modified...
cquad_equ
R Documentation
Conditional maximum likelihood estimation for the modified version of the quadratic exponential model (to test for state dependence)
Description
Fit by conditional maximum likelihood a modified version of the model for binary logitudinal data proposed by Bartolucci & Nigro (2010), in which the interaction terms have an extended form. This modified version is used to test for state dependence as described in Bartolucci et al. (2013).
Usage
cquad_equ(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 Perugia)
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, 719-733.
Bartolucci, F., Nigro, V. and Pigini, C. (2013), Testing for state dependence in binary panel data with individual covariates, Econometric Reviews, in press.
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_equ(id,yv,X)