• SAS/STAT

  • Referenced in 418 articles [sw18788]
  • including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster...
  • MULTIMIX

  • Referenced in 34 articles [sw03250]
  • program is designed to cluster multivariate data that have categorical and continuous variables and that...
  • MICE

  • Referenced in 132 articles [sw09315]
  • package mice: Multivariate Imputation by Chained Equations. Multiple imputation using Fully Conditional Specification (FCS) implemented ... continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic...
  • bfa

  • Referenced in 22 articles [sw07430]
  • multivariate data. There is rich literature on their extension to mixed categorical and continuous variables...
  • AlphaTwirl

  • Referenced in 1 article [sw30635]
  • categorical data. AlphaTwirl is a Python library that summarizes large event data into multivariate categorical ... data frames in R and pandas. With their rich set of data wrangling tools, users ... flexible and configurable analysis code. The multivariate categorical data loaded as data frames are readily...
  • missMDA

  • Referenced in 15 articles [sw08142]
  • with/in multivariate data analysis (principal component methods). Imputation of incomplete continuous or categorical datasets; Missing...
  • Latent GOLD

  • Referenced in 93 articles [sw11673]
  • variable X. Since the latent variable is categorical, LC modeling differs from more traditional latent ... field of finite mixture (FM) models for multivariate normal distributions began to emerge, through ... seek to separate out or ’un-mix’ data that is assumed to arise...
  • LCAvarsel

  • Referenced in 1 article [sw24497]
  • analysis for model-based clustering of multivariate categorical data. The package implements a general framework...
  • MGLM

  • Referenced in 2 articles [sw19421]
  • penalized regression on the multivariate categorical response data. Implemented models include: multinomial logit model, Dirichlet...
  • PCAmixdata

  • Referenced in 4 articles [sw08547]
  • Multivariate analysis of mixed data: The PCAmixdata R package. Mixed data type arise when observations ... numerical and categorical variables. The R package PCAmixdata extends standard multivariate analysis methods to incorporate ... this type of data. The key techniques included in the package are PCAmix ... mixture of numerical and categorical variables), PCArot (rotation in PCAmix) and MFAmix (multiple factor analysis...
  • gcmr

  • Referenced in 27 articles [sw07433]
  • categorical responses is allowed. Dependence is conveniently modelled in terms of multivariate normal errors. Inference ... validating the adequacy of the assumed multivariate model. Methodology is implemented in a R package ... called gcmr. Illustrations include simulations and real data applications regarding time series, cross-design data...
  • latticist

  • Referenced in 1 article [sw12943]
  • from the vcd package for categorical data. Given a multivariate dataset (either a data frame...
  • rasterVis

  • Referenced in 3 articles [sw09325]
  • quantitative data and categorical data, with levelplot, both for univariate and multivariate rasters. It also...
  • MacSpin

  • Referenced in 10 articles [sw14078]
  • trends, clusters, and other patterns in multivariate data as well as highly unusual observations (outliers ... data manipulation and calculation features that allow the user to transform, edit, and categorize data...
  • mvis

  • Referenced in 10 articles [sw37353]
  • describes five ado-files. mvis creates multiple multivariate imputations. uvis imputes missing values ... function of several covariates, each with complete data. micombine fits a wide variety of regression ... supports survival analysis models (stcox and streg), categorical data models, generalized linear models, and more...
  • MMDai

  • Referenced in 2 articles [sw19197]
  • MMDai. Multivariate Multinomial Distribution Approximation and Imputation for Incomplete Data. Fit incomplete categorical data with...
  • editrules

  • Referenced in 1 article [sw29956]
  • reading and manipulating (multivariate) data restrictions (edit rules) on numerical and categorical data. Rules...
  • runmlwin

  • Referenced in 4 articles [sw23864]
  • binary, count, ordered categorical and unordered categorical data; Fast estimation via classical and Bayesian methods ... multiple membership nonhierarchical data structures; Estimation of multilevel multivariate response models, multilevel spatial models, multilevel...
  • GPLOM

  • Referenced in 1 article [sw35569]
  • multidimensional multivariate data. However, these techniques are not well suited to visualizing many categorical variables...
  • MissingDataGUI

  • Referenced in 2 articles [sw23665]
  • Data Exploration. Provides numeric and graphical summaries for the missing values from both categorical ... univariate imputations like fixed or random values, multivariate imputations like the nearest neighbors and multiple...