• plfit

  • Referenced in 269 articles [sw23186]
  • distributions, and even in cases where such methods return accurate answers they are still unsatisfactory ... empirical data. Our approach combines maximum-likelihood fitting methods with goodness-of-fit tests based...
  • copula

  • Referenced in 148 articles [sw07944]
  • copulas and Archimedean copulas are implemented, with methods for density/distribution evaluation, random number generation ... display. Fitting copula-based models with maximum likelihood method is provided as template examples. With...
  • fitdistrplus

  • Referenced in 28 articles [sw15776]
  • discrete data) and allowing different estimation methods (maximum likelihood, moment matching, quantile matching and maximum ... functions are S3 objects, for which specific methods are provided, including summary, plot and quantile...
  • PAUP*

  • Referenced in 57 articles [sw07834]
  • field. With the inclusion of maximum likelihood and distance methods in PAUP...
  • MLwiN

  • Referenced in 105 articles [sw04837]
  • uses both maximum likelihood estimation and Markov Chain Monte Carlo (MCMC) methods. MLwiN is based...
  • MsdeParEst

  • Referenced in 22 articles [sw25419]
  • diffusion or both. Approximate maximum likelihood methods are used. M. Delattre, V. Genon-Catalot...
  • latentnet

  • Referenced in 21 articles [sw10550]
  • position model and a two-stage maximum likelihood method for the latent position cluster model ... estimates for the coefficients and positions: maximum likelihood estimate, posterior mean, posterior mode...
  • dclone

  • Referenced in 15 articles [sw23656]
  • Data Cloning and MCMC Tools for Maximum Likelihood Methods. Low level functions for implementing maximum ... cloning and Bayesian Markov chain Monte Carlo methods as described in Solymos 2010 (R Journal...
  • gldex

  • Referenced in 11 articles [sw10548]
  • Distributions to Data via Discretized and Maximum Likelihood Methods: GLDEX in R. This paper describes ... empirical data using the discretized and maximum likelihood methods. The GLDEX package also provides diagnostic...
  • CDVine

  • Referenced in 52 articles [sw08161]
  • joint maximum likelihood estimation. Sampling algorithms and plotting methods are also included. Data is assumed...
  • bbmle

  • Referenced in 12 articles [sw11270]
  • package bbmle: Tools for general maximum likelihood estimation. Methods and functions for fitting maximum likelihood...
  • VineCopula

  • Referenced in 40 articles [sw08160]
  • joint maximum likelihood estimation. Sampling algorithms and plotting methods are also included. Data is assumed...
  • lcmm

  • Referenced in 15 articles [sw13207]
  • multivariate longitudinal outcomes using a maximum likelihood estimation method...
  • RAxML

  • Referenced in 44 articles [sw07716]
  • phylogeny with maximum likelihood. Inference of large phylogenetic trees with statistical methods is computationally intensive...
  • goodwin.f77

  • Referenced in 22 articles [sw37144]
  • quadrature and our new method to obtain the maximum likelihood estimator of relative risk ... model. Using standard subroutines to maximize the likelihood equations, 27 of 50 trials failed ... point Gaussian quadrature, whereas the new method allowed convergence in all but one case...
  • PSMIX

  • Referenced in 5 articles [sw13670]
  • package for population structure inference via maximum likelihood method. Background: Inference of population stratification ... association mapping and evolutionary studies. Bayesian methods have been proposed for population stratification and admixture ... widely used in practice. However, these Bayesian methods demand intensive computation resources ... PSMIX, an R package based on maximum likelihood method using expectation-maximization algorithm, for inference...
  • mnlogit

  • Referenced in 7 articles [sw21116]
  • estimation of multinomial logit models using maximum likelihood method. Numerical optimization performed by Newton-Raphson...
  • dlm

  • Referenced in 30 articles [sw04503]
  • linear models with known parameters, and maximum likelihood estimation. It also presents many specific dynamic ... univariate and multivariate data. The main methods and models are illustrated with examples based ... reminded, and Markov chain Monte Carlo methods are presented. Chapter 2 is on dynamic linear ... parameters. It presents a discussion of maximum likelihood estimation and a much more elaborated...
  • RegEM

  • Referenced in 18 articles [sw04943]
  • algorithm, a regularized estimation method replaces the conditional maximum likelihood estimation of regression parameters ... with generalized cross-validation as regularized estimation methods. The implementation of the regularized EM algorithm...
  • PROC LOGISTIC

  • Referenced in 10 articles [sw12078]
  • discrete response data by the method of maximum likelihood. It can also perform conditional logistic...