Search results for "lcsh:Statistics"

showing 2 items of 22 documents

IndElec: A Software for Analyzing Party Systems and Electoral Systems

2011

IndElec is a software addressed to compute a wide range of indices from electoral data, which are intended to analyze both party systems and electoral systems in political studies. Further, IndElec can calculate such indices from electoral data at several levels of aggregation, even when the acronyms of some political parties change across districts. As the amount of information provided by IndElec may be considerable, this software also aids the user in the analysis of electoral data through three capabilities. First, IndElec automatically elaborates preliminary descriptive statistical reports of computed indices. Second, IndElec saves the computed information into text files in data matri…

Statistics and ProbabilityWeb browserDatabaseComputer sciencebusiness.industrydisproportionalityparty systemcomputer.software_genreFile formatVisualizationRange (mathematics)Softwareelectoral systemStatistics Probability and Uncertaintybusinessparty dimensionscomputerlcsh:Statisticslcsh:HA1-4737SoftwareWord (computer architecture)Statistical softwareGraphical user interfaceJournal of Statistical Software
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Beyond Tandem Analysis: Joint Dimension Reduction and Clustering in R

2019

We present the R package clustrd which implements a class of methods that combine dimension reduction and clustering of continuous or categorical data. In particular, for continuous data, the package contains implementations of factorial K-means and reduced K-means; both methods combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means, i-FCB and cluster correspondence analysis, which combine multiple correspondence analysis with K-means. Two examples on real data sets are provided to illustrate the usage of the main functions.

dimension reduction; clustering; principal component analysis; multiple correspondence analysis; K-meansStatistics and Probabilitydimension reduction clustering principal component analysis multiple correspon-dence analysis K-meansFactorialmultiple correspon-dence analysisMultiple correspondence analysiComputer sciencedimension reductionprincipal component analysisk-meansmultiple correspondence analysisPrincipal component analysicomputer.software_genre01 natural sciencesCorrespondence analysis010104 statistics & probabilityMultiple correspondence analysis0101 mathematicsCluster analysisCategorical variablelcsh:Statisticslcsh:HA1-4737Dimensionality reductionk-means clusteringK-meanPrincipal component analysisData miningHA29-32Statistics Probability and UncertaintycomputerSoftwareclusteringJournal of Statistical Software
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