• lavaan

  • Referenced in 72 articles [sw07227]
  • variety of latent variable models, including confirmatory factor analysis, structural equation modeling and latent growth...
  • Latent GOLD

  • Referenced in 94 articles [sw11673]
  • differs from more traditional latent variable approaches such as factor analysis, structural equation models ... regression models that are based on continuous latent variables. Latent class (LC) analysis was originally...
  • bfa

  • Referenced in 25 articles [sw07430]
  • copula factor models for mixed data. Gaussian factor models have proven widely useful for parsimoniously ... mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models ... generalizing to non-Gaussian measured variables, the latent variables typically influence both the dependence structure ... copula factor models that decouple the latent factors from the marginal distributions. A semiparametric specification...
  • PARAFAC

  • Referenced in 24 articles [sw14789]
  • straightforward generalization of the bilinear model of factor (or component) analysis (xij = ΣRr = 1airbjr ... model: if the latent factors show adequately distinct patterns of three-way variation, the model...
  • GTM

  • Referenced in 57 articles [sw39434]
  • smaller number of latent, or hidden, variables. A familiar example is factor analysis which...
  • FarmTest

  • Referenced in 7 articles [sw31555]
  • package FarmTest: Factor Adjusted Robust Multiple Testing. Performs robust multiple testing for means ... presence of known and unknown latent factors. It implements a series of adaptive Huber methods...
  • SOFAR

  • Referenced in 7 articles [sw31665]
  • network structures via layers of sparse latent factors ranked by importance. Yet sparsity and orthogonality...
  • NICE

  • Referenced in 15 articles [sw29631]
  • data conform to a factorized distribution, i.e., resulting in independent latent variables. We parametrize this...
  • factorstochvol

  • Referenced in 3 articles [sw31446]
  • package factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models. Markov chain Monte Carlo ... sampler for fully Bayesian estimation of latent factor stochastic volatility models with interweaving...
  • BayesFM

  • Referenced in 3 articles [sw17545]
  • factor loading matrix. The number of latent factors, as well as the allocation...
  • mirtjml

  • Referenced in 2 articles [sw36870]
  • joint maximum likelihood estimation algorithms for item factor analysis (IFA) based on multidimensional item response ... large numbers of respondents, items, and latent factors. The computation is facilitated by multiprocessing ’OpenMP ... Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23. Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their...
  • dSprites

  • Referenced in 3 articles [sw31840]
  • generated from 6 ground truth independent latent factors. These factors are color, shape, scale, rotation ... sprite. All possible combinations of these latents are present exactly once, generating N = 737280 total...
  • IMIFA

  • Referenced in 3 articles [sw20290]
  • conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model ... number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific...
  • GLLAMM

  • Referenced in 62 articles [sw06517]
  • package Stata and estimates GLLAMMs (Generalized Linear Latent And Mixed Models) by maximum likelihood ... case of discrete random effects or factors, the marginal log-likelihood is evaluated exactly whereas...
  • GeoMF

  • Referenced in 2 articles [sw25054]
  • Particularly, we augment users’ and POIs’ latent factors in the factorization model with activity area...
  • mirt

  • Referenced in 36 articles [sw13479]
  • polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory ... stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item...
  • LFADS

  • Referenced in 1 article [sw16550]
  • LFADS - Latent Factor Analysis via Dynamical Systems. Neuroscience is experiencing a data revolution in which ... analyzed. Here we introduce LFADS (Latent Factor Analysis via Dynamical Systems), a method to infer ... latent dynamics from simultaneously recorded, single-trial, high-dimensional neural spiking data. LFADS ... dimensional temporal factors, per-trial initial conditions, and inferred inputs. We compare LFADS to existing...
  • Alors

  • Referenced in 1 article [sw19071]
  • initial instance representation, whereas CF builds latent factors to describe algorithms and instances, and uses ... linear modeling of the latent factors based on the initial instance representation, extending the linear...
  • slfm

  • Referenced in 1 article [sw30052]
  • package slfm: Tools for Fitting Sparse Latent Factor Model Set of tools to find coherent ... microarray data using a Bayesian Sparse Latent Factor Model - SLFM; see Duarte and Mayrink...
  • blavaan

  • Referenced in 4 articles [sw24888]
  • variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent...