Title: Estimating Conditional Auto-Regression (CAR) Models using Monte

Imports: spam, rsm, fields, maxLik, nleqslv, spdep, spatialreg

Title: Monte Carlo Local Likelihood Estimation
Author: Minjeong Jeon <mjj@berkeley.edu>, Cari Kaufman
Description: Maximum likelihood estimation using a Monte Carlo local
Packaged: 2012-11-01 19:00:32 UTC; Administrator

Packaged: 2013-02-04 17:30:28 UTC; Administrator

Author: Minjeong Jeon, Cari Kaufman, and Sophia Rabe-Hesketh
Description: Maximum likelihood estimation using a Monte Carlo local likelihood (MCLL) method

Title: Mastering Corpus Linguistics Methods
Description: Read, inspect and process corpus files for quantitative corpus linguistics.
Obtain concordances via regular expressions, tokenize texts,
and compute frequencies and association measures. Useful for collocation analysis,
keywords analysis and variationist studies (comparison of linguistic variants
Imports: crayon, dplyr, Rcpp, readr, stringi, stringr, tm, xml2, yaml
Suggests: MASS, tidyr, purrr, testthat (>= 3.0.0), covr

Description: This packages provides a function to estimate parameters
for the mixed conditional logit model, or conditional logit
with random effects. The current implementation is limited to
random intercepts and to the PQL technique, mainly appropriate

Description: This packages provides a function to estimate parameters for the
mixed conditional logit model, or conditional logit with random effects.
The current implementation is limited to random intercepts and to
the PQL technique, mainly appropriate for large clusters.

with random effects.  The current implementation is limited to

The current implementation of random effects is limited to
the PQL technique, which requires large cluster sizes.

Description: This packages provides a function to estimate parameters for
the conditional logit model (also with multinomial counts), and for the
mixed conditional logit model, or conditional logit with random effects
(random intercepts only, no random slopes yet).

Description: Specification and estimation of conditional logit models of binary responses and multinomial counts is provided,
with or without alternative-specific random effects (random intercepts only, no random slopes yet).
The current implementation of the estimator for random effects variances uses a Laplace approximation (or PQL)
approach and thus should be used only if groups sizes are large.