• elicit-normlin

  • Referenced in 27 articles [sw27808]
  • prior distribution for the normal linear model, based on the 1980 JASA paper by Kadane ... Interactive Elicitation of Opinion for a Normal Linear Model...
  • PROC GENMOD

  • Referenced in 29 articles [sw11741]
  • linear models. These include classical linear models with normal errors, logistic and probit models...
  • Voom

  • Referenced in 17 articles [sw14009]
  • read counts. New normal linear modeling strategies are presented for analyzing read counts from...
  • dlm

  • Referenced in 29 articles [sw04503]
  • smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear...
  • glimmix

  • Referenced in 28 articles [sw11740]
  • necessarily normally distributed. These models are known as generalized linear ... mixed models (GLMM). GLMMs, like linear mixed models, assume normal (Gaussian) random effects. Conditional...
  • gcmr

  • Referenced in 27 articles [sw07433]
  • Gaussian copula models for marginal regression analysis of non-normal dependent observations. The class provides ... natural extension of traditional linear regression models with normal correlated errors. Any kind of continuous...
  • BIEMS

  • Referenced in 9 articles [sw21171]
  • calculating Bayes factors of multivariate normal linear models with equality and/or inequality constraints between...
  • ic.infer

  • Referenced in 5 articles [sw14709]
  • This package implements parameter estimation in normal (linear) models under linear equality and inequality constraints ... implements normal likelihood ratio tests involving inequality-constrained hypotheses. For inequality-constrained linear models, averaging...
  • blasso

  • Referenced in 13 articles [sw06769]
  • Elastic net regression modeling with the orthant normal prior The elastic net procedure ... form of regularized optimization for linear regression that provides a bridge between ridge regression ... estimate as the posterior mode. The resulting model-based framework allows for a methodology that ... properly normalized, direct characterization, which is shown to be conjugate for linear regression models...
  • glmmAK

  • Referenced in 25 articles [sw13218]
  • linear model). Secondly, Bayesian estimation based on MCMC in the logistic and Poisson regression model ... whose distribution is specified as a penalized normal mixture are implemented. The methodology is described ... LESAFFRE, E. (2008). Generalized linear mixed model with a penalized Gaussian mixture as a random...
  • AS 139

  • Referenced in 10 articles [sw14177]
  • Likelihood Estimation in a Linear Model from Confined and Censored Normal Data...
  • bernor

  • Referenced in 8 articles [sw19665]
  • Monte Carlo likelihood inference for missing data models. We describe a Monte Carlo method ... consistent and asymptotically normal estimate of the minimizer θ * of the Kullback-Leibler information ... give logit-normal generalized linear mixed model examples, calculated using an R package...
  • WebArray

  • Referenced in 3 articles [sw37316]
  • quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery...
  • Clingcon

  • Referenced in 34 articles [sw09892]
  • extended) constraint normal logic programs. It combines the high-level modeling capacities of Answer ... with constraint solving. Constraints over non-linear finite integers can be used in the logic...
  • lmec

  • Referenced in 19 articles [sw13215]
  • function to fit a linear mixed-effects model in the formulation described in Laird ... Ware (1982) but allowing for censored normal responses. In this version, the with-in group...
  • cudaBayesreg

  • Referenced in 6 articles [sw24712]
  • Gibbs Sampler for hierarchical linear models with a normal prior. This model has been proposed...
  • GORIC

  • Referenced in 2 articles [sw24569]
  • namely, closed convex cones) for multivariate normal linear models. It can examine the traditional hypotheses...
  • GLLAMM

  • Referenced in 61 articles [sw06517]
  • Stata and estimates GLLAMMs (Generalized Linear Latent And Mixed Models) by maximum likelihood (see help ... numerical integration is used for continuous (multivariate) normal random effects or factors. Two methods...
  • wwcode

  • Referenced in 19 articles [sw26044]
  • Rank-Based Analysis of Linear Models Using R. It is well-known that Wilcoxon procedures ... squares procedures when the data deviate from normality and/or contain outliers. These procedures ... implement a robust analysis of a linear model based on WW-estimates. For instance, estimation...
  • mcglm

  • Referenced in 5 articles [sw23203]
  • generalized linear models (McGLMs) to data. McGLMs is a general framework for non-normal multivariate ... matrix linear predictor involving known matrices. The models take non-normality into account ... structure is modelled by means of a link function and a linear predictor. The models...