
MLwiN
 Referenced in 108 articles
[sw04837]
 uses both maximum likelihood estimation and Markov Chain Monte Carlo (MCMC) methods. MLwiN is based...

RStan
 Referenced in 87 articles
[sw13990]
 Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood estimation...

rstan
 Referenced in 55 articles
[sw16103]
 Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood estimation...

dlm
 Referenced in 32 articles
[sw04503]
 linear models with known parameters, and maximum likelihood estimation. It also presents many specific dynamic ... models are reminded, and Markov chain Monte Carlo methods are presented. Chapter ... parameters. It presents a discussion of maximum likelihood estimation and a much more elaborated ... last chapter is on sequential Monte Carlo methods...

latentnet
 Referenced in 21 articles
[sw10550]
 Markov chain Monte Carlo algorithm. It can also compute maximum likelihood estimates for the latent...

bernor
 Referenced in 10 articles
[sw19665]
 describe a Monte Carlo method to approximate the maximum likelihood estimate (MLE), when there ... missing data and the observed data likelihood is not available in closed form. This method ... independent of the observed data. Our Monte Carlo approximation to the MLE is a consistent...

btergm
 Referenced in 4 articles
[sw24452]
 confidence intervals or Markov Chain Monte Carlo maximum likelihood. Goodness of fit assessment for ERGMs...

dclone
 Referenced in 15 articles
[sw23656]
 maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte ... Carlo methods as described in Solymos 2010 (R Journal 2(2):29–37). Sequential...

mlergm
 Referenced in 1 article
[sw38222]
 blocks. The estimation method uses MonteCarlo maximum likelihood estimation (MCMLE) methods to estimate...

CML
 Referenced in 10 articles
[sw26227]
 developed at Aptech Systems, generates maximum likelihood estimates with general parametric constraints (linear or nonlinear ... intervals, by inversion of the Wald and likelihood ratio statistics, and by simulation. The inversion ... produce misleading test sizes, but Monte Carlo evidence suggests this problem can be corrected under...

mclcar
 Referenced in 0 articles
[sw16187]
 Monte Carlo likelihood. The Maximum Monte Carlo likelihood estimator is found either by an iterative...

Apophenia
 Referenced in 2 articles
[sw05712]
 computationallyintensive procedures like maximum likelihood estimation and Monte Carlo routines are easy to implement...

glmm
 Referenced in 3 articles
[sw36739]
 using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates...

StanHeaders
 Referenced in 4 articles
[sw15586]
 Markov Chain Monte Carlo or variational methods and implements (optionally penalized) maximum likelihood estimation...

PSMIX
 Referenced in 5 articles
[sw13670]
 package for population structure inference via maximum likelihood method. Background: Inference of population stratification ... into convergence problem in Markov Chain Monte Carlo based posterior samplings. Results: We have developed ... PSMIX, an R package based on maximum likelihood method using expectationmaximization algorithm, for inference...

snp
 Referenced in 2 articles
[sw37499]
 Econometrica 55: 363390), the semiparametric maximum likelihood ap proach of Klein and Spady ... underlying error terms. Our Monte Carlo simulations suggest that the efficiency losses of the semi ... nonparametric and the semiparametric maximum likelihood estimators relative to a maximum like lihood correctly specified...

tauPFC
 Referenced in 1 article
[sw40644]
 Monte Carlo study compares the performance of 𝜏 estimators and maximum likelihood estimators. The results...

iZID
 Referenced in 2 articles
[sw32719]
 bootstrapped Monte Carlo estimate of p value of KolmogorovSmirnov (KS) test and likelihood ratio ... zero inflated or hurdle models and obtain maximum likelihood estimate of unknown parameters in these...

survHE
 Referenced in 1 article
[sw35581]
 models under a frequentist (based on maximum likelihood) or a Bayesian approach (both based ... Integrated Nested Laplace Approximation or Hamiltonian Monte Carlo). The user can specify...

SISTOS
 Referenced in 1 article
[sw14820]
 complexity of the problem, sequential Monte Carlo (SMC) methods are used. We investigate SMC methods ... proposal distribution is computed by maximum likelihood or by a linearization approach. We prove that...