User 2019 Toulouse Talk Multivariate Data Analysis Fabien Llobell Clustblock: a package for clustering datasets". "using the package 'simple features' (sf) for sensivity analysis".
User 2019 Toulouse Talk Multivariate Data Analysis Maikol "funhddc, a r package to cluster unvariate and multivariate functional data". In addition to clustering algorithm, the package provides model selection criteria for choosing the number of clusters, and allows the execution of principal component analysis for multivariate functional data. the package usage will be shown on several practical examples whose an original example of horse speed prediction. 12:24: multivariate. In many application settings, the data have missing features which make data analysis challenging. an abundant literature addresses missing data as well as more than 150 r packages. funded by the r consortium, we have created the r miss tastic plateform along with a dedicated task view which aims at giving an overview of main references. The clustatis method: clustering of blocks of quantitative variables decribing the same observations but variables may be different from one block to another. test to know if there is more than one cluster recommended number of clusters indices to assess homogeneity of clusters possibility to introduce a noise cluster graphical representations.
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