• SAS/STAT

  • Referenced in 433 articles [sw18788]
  • including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster ... models, generalized linear models, correspondence analysis, and structural equations...
  • INTLAB

  • Referenced in 464 articles [sw04004]
  • including unconstrained optimization) roots of univariate and multivariate nonlinear equations (simple and clusters) eigenvalue problems ... simple and clusters, also inner inclusions and structured matrices) generalized eigenvalue problems (simple and clusters ... clusters) interval arithmetic for real and complex data including vectors and matrices (very fast) interval ... integration of (simple) univariate functions univariate and multivariate (interval) polynomials rigorous real interval standard functions...
  • Projective Noether

  • Referenced in 15 articles [sw00734]
  • straight-line programs as a data structure to represent multivariate polynomials. We present here...
  • MANET

  • Referenced in 27 articles [sw03067]
  • specially designed for studying multivariate features. Anyone involved in analysing data will find MANET useful ... gaining insights into the structure and relationships of their data sets...
  • Amos

  • Referenced in 60 articles [sw06515]
  • build models more accurately than with standard multivariate statistics techniques. Users can choose either ... that reflect complex relationships. The software: Provides structural equation modeling (SEM)—that is easy ... improve estimates of model parameters. Offers various data imputation methods—to create different data sets...
  • SYNAPS

  • Referenced in 24 articles [sw00941]
  • kernel of this platform provides data-structures and classes for the manipulation of basic objects ... vectors, matrices (dense, sparse, structured), univariate and multivariate polynomial (in the monomial, Horner or Bernstein...
  • Latent GOLD

  • Referenced in 94 articles [sw11673]
  • latent variable approaches such as factor analysis, structural equation models, and random-effects regression models ... 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...
  • CensMixReg

  • Referenced in 9 articles [sw21090]
  • mixture modeling of censored data using the multivariate student-t distribution. Finite mixture models have ... modeling and analysis of data from a heterogeneous population. Moreover, data of this kind ... structures, we propose a robust model for censored data based on finite mixtures of multivariate ... data with great flexibility, accommodating multimodality, heavy tails and also skewness depending on the structure...
  • sirt

  • Referenced in 6 articles [sw15945]
  • LSEM), mean and covariance structure modelling for multivariate normally distributed data...
  • runmlwin

  • Referenced in 4 articles [sw23864]
  • multiple membership nonhierarchical data structures; Estimation of multilevel multivariate response models, multilevel spatial models, multilevel...
  • CoClust

  • Referenced in 3 articles [sw19990]
  • allows to cluster dependent data according to the multivariate structure of the generating process without ... test our proposal on simulated data for different dependence scenarios and compare it with...
  • mbsts

  • Referenced in 1 article [sw39153]
  • Time Series. Tools for data analysis with multivariate Bayesian structural time series (MBSTS) models. Specifically ... package provides facilities for implementing general structural time series models, flexibly adding on different time ... simulating them, fitting them to multivariate correlated time series data, conducting feature selection...
  • VIM

  • Referenced in 22 articles [sw06776]
  • missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods ... missings and allows to explore the data including missing values. In addition, the quality ... explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface allows...
  • GPFDA

  • Referenced in 7 articles [sw14770]
  • multidimensional inputs, multivariate functional data, and non-separable and/or non-stationary covariance structure of function...
  • NTSYSpc

  • Referenced in 1 article [sw18411]
  • used to discover pattern and structure in multivariate data. For example, one may wish...
  • bfa

  • Referenced in 25 articles [sw07430]
  • useful for parsimoniously characterizing dependence in multivariate data. There is rich literature on their extension ... latent variables typically influence both the dependence structure and the form of the marginal distributions...
  • multiplex

  • Referenced in 3 articles [sw16370]
  • possible to create and manipulate multivariate network data with different formats, and there are effective ... structure together with the relational bundles occurring in different types of multivariate network data sets...
  • Givaro

  • Referenced in 7 articles [sw00354]
  • wrappers over gmp) It also provides data-structures and templated classes for the manipulation ... vectors, matrices (dense, sparse, structured), univariate polynomials (and therefore recursive multivariate). It contains different program...
  • mcglm

  • Referenced in 5 articles [sw23203]
  • normal multivariate data analysis, designed to handle multivariate response variables, along with a wide range ... temporal and spatial correlation structures defined in terms of a covariance link function combined with...
  • abn

  • Referenced in 2 articles [sw31036]
  • package abn: Modelling Multivariate Data with Additive Bayesian Networks. Bayesian network analysis is a form ... from empirical data a directed acyclic graph, DAG, describing the dependency structure between random variables ... Bayesian multivariate regression using graphical modelling, they generalises the usual multivariable regression, GLM, to multiple ... messy, complex data. The additive formulation of these models is equivalent to multivariate generalised linear...