• Mplus

  • Referenced in 339 articles [sw06511]
  • observed variables that are continuous, censored, binary, ordered categorical (ordinal), unordered categorical (nominal), counts...
  • Latent GOLD

  • Referenced in 93 articles [sw11673]
  • latent variable X. Since the latent variable is categorical, LC modeling differs from more traditional...
  • MICE

  • Referenced in 137 articles [sw09315]
  • implemented by the MICE algorithm. Each variable has its own imputation model. Built-in imputation ... matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical ... level data (normal model, pan, second-level variables). Passive imputation can be used to maintain...
  • MULTIMIX

  • Referenced in 34 articles [sw03250]
  • cluster multivariate data that have categorical and continuous variables and that possibly contain missing values...
  • bfa

  • Referenced in 23 articles [sw07430]
  • their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized...
  • AFMULT

  • Referenced in 21 articles [sw08201]
  • studies several groups of variables (numerical and/or categorical) defined on the same set of individuals ... factor analysis in which groups of variables are weighted, canonical analysis, Procrustes analysis, STATIS, INDSCAL...
  • glinternet

  • Referenced in 10 articles [sw18380]
  • also have nonzero estimated coefficients. Accommodates categorical variables (factors) with arbitrary numbers of levels, continuous...
  • VCD

  • Referenced in 8 articles [sw25927]
  • Visualizing Categorical Data. Categorical data consists of variables whose values comprise a set of discrete ... reveal patterns of relationships among categorical variables...
  • T-PROGS

  • Referenced in 8 articles [sw09170]
  • probability/Markov approach to geostatistical simulation of categorical variables...
  • PCAmixdata

  • Referenced in 5 articles [sw08547]
  • mixture of numerical and categorical variables. The R package PCAmixdata extends standard multivariate analysis methods ... mixture of numerical and categorical variables), PCArot (rotation in PCAmix) and MFAmix (multiple factor analysis...
  • GlobalAncova

  • Referenced in 7 articles [sw30019]
  • global pattern of a group of variables (e.g. a gene set) is tested ... framework is generalized to groups of categorical variables or even mixed data by a likelihood...
  • cat

  • Referenced in 4 articles [sw19480]
  • package cat: Analysis of categorical-variable datasets with missing values. Analysis of categorical-variable with...
  • DUE

  • Referenced in 3 articles [sw27796]
  • numerical variables (e.g. bird counts) and categorical variables (e.g. land-cover). Once data are imported...
  • kamila

  • Referenced in 2 articles [sw16426]
  • contribution of the continuous and categorical variables. This package implements KAMILA clustering, a novel method ... does not require dummy coding of variables, and is efficient enough to scale to rather ... separation simultaneously in the continuous and categorical variables...
  • forcats

  • Referenced in 3 articles [sw21275]
  • package forcats: Tools for Working with Categorical Variables (Factors). Helpers for reordering factor levels (including...
  • GPLOM

  • Referenced in 1 article [sw35569]
  • well suited to visualizing many categorical variables (i.e., independent variables or dimensions). To visualize multiple ... categorical variables, ’hierarchical axes’ that ’stack dimensions’ have been used in systems like Polaris ... well beyond a small number of categorical variables. Emerson et al. [8] extend the matrix ... continuous variables, heatmaps for pairs of categorical variables, and barcharts for pairings of categorical...
  • MissingDataGUI

  • Referenced in 2 articles [sw23665]
  • missing values from both categorical and quantitative variables. A variety of imputation methods are applied ... imputations, and imputations conditioned on a categorical variable...
  • clustMixType

  • Referenced in 2 articles [sw16328]
  • perform k-prototypes partitioning clustering for mixed variable-type data according to Z.Huang (1998): Extensions ... Clustering Large Data Sets with Categorical Variables, Data Mining and Knowledge Discovery...
  • knncat

  • Referenced in 1 article [sw11056]
  • knncat: Nearest-neighbor Classification with Categorical Variables. Scale categorical variables in such...
  • CAR

  • Referenced in 2 articles [sw07768]
  • used to analyse relationships between categorical variables. Like principal component analysis, CA solutions...