
MICE
 Referenced in 134 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...

BayesBinMix
 Referenced in 3 articles
[sw19815]
 Package for Model Based Clustering of Multivariate Binary Data. The BayesBinMix package offers a Bayesian ... clustering binary data with or without missing values by fitting mixtures of multivariate Bernoulli distributions...

MvBinary
 Referenced in 1 article
[sw15146]
 MvBinary: Modelling Multivariate Binary Data with Blocks of Specific OneFactor Distribution. Modelling Multivariate Binary...

EMbC
 Referenced in 1 article
[sw27360]
 EMbC: ExpectationMaximization Binary Clustering. Unsupervised, multivariate, binary clustering for meaningful annotation of data, taking...

spatialkernel
 Referenced in 3 articles
[sw24503]
 kernel density estimation and binary kernel regression estimation for multivariate spatial point process data...

QUAD
 Referenced in 15 articles
[sw19553]
 iteration of a set of multivariate quadratic polynomials over a finite field, typically ... small extension. We show that in the binary case, the security of the keystream generation...

GJRM
 Referenced in 9 articles
[sw23082]
 joint regression modeling framework for analyzing bivariate binary data in R. We discuss some ... modeling framework for fitting a number of multivariate response regression models under various sampling schemes ... inwhich the user wishes to fit bivariate binary regression models in the presence of several...

BAYESTAT
 Referenced in 2 articles
[sw17949]
 Bayesian models for correlated binary data. The importance of the multivariate probit model is highlighted ... simulation algorithms for the fitting of the multivariate probit, probit normal and hierarchical probit models ... shows how alternative Bayesian models for correlated binary data can be compared. Marginal likelihoods from...

xmeta
 Referenced in 1 article
[sw15395]
 implementing robust multivariate metaanalysis of continuous or binary outcomes; and (2) testing and correcting...

cpcens
 Referenced in 1 article
[sw37366]
 changepoint, double cumulative sum binary segmentation, multiple changepoints in multivariate time series, analyzing each series...

fabisearch
 Referenced in 1 article
[sw38226]
 Time Series Networks. Implementation of the Factorized Binary Search (FaBiSearch) methodology for the estimation ... network (or clustering) structure of multivariate highdimensional time series. The method is motivated ... unsupervised dimension reduction technique, and a new binary search algorithm to identify multiple change points ... est.net(), for estimating a network between stationary multivariate time series, net.3dplot(), for plotting the estimated...

tmleCommunity
 Referenced in 1 article
[sw33567]
 package supports multivariate arbitrary (i.e., static, dynamic or stochastic) interventions with a binary or continuous...

BayesProject
 Referenced in 1 article
[sw35837]
 approach to compute a projection direction for multivariate changepoint detection, as well ... cusum methods, and a wild binary segmentation wrapper for all algorithms...

Mediana
 Referenced in 1 article
[sw16602]
 with continuous, binary, survivaltype and counttype endpoints as well as multivariate outcomes that...

runmlwin
 Referenced in 4 articles
[sw23864]
 features: Estimation of multilevel models for continuous, binary, count, ordered categorical and unordered categorical data ... membership nonhierarchical data structures; Estimation of multilevel multivariate response models, multilevel spatial models, multilevel measurement...

stremr
 Referenced in 0 articles
[sw18479]
 coded as either binary, categorical or continuous. Each can be multivariate (e.g., can use more...

ebalance
 Referenced in 1 article
[sw24556]
 Stata package ebalance implements entropy balancing, a multivariate reweighting method described in Hainmueller (2012 ) that ... balanced samples in observational studies with a binary treatment where the control group data...

MultBiplot
 Referenced in 1 article
[sw32660]
 MultBiplot: MULTivariate analysis using BIPLOTs. MULTBIPLOT is a program to perform Biplot Analysis. It contains ... Contingency Table, Canonical/MANOVA Biplot, Logistic Biplots for Binary Data, Common Biplot for Several groups, among...

multfisher
 Referenced in 1 article
[sw25602]
 reference group with respect to multiple binary endpoints. The tested null hypothesis is an identical ... endpoint. The tests are based on the multivariate permutation distribution of subjects between...

SABRE
 Referenced in 2 articles
[sw24536]
 These responses can take the form of binary, ordinal, count and linear recurrent events ... software, see Berridge, D.M., Crouchley, R., (2011), Multivariate Generalized Linear Mixed Models Using...