ICtest

R package ICtest: Estimating and Testing the Number of Interesting Components in Linear Dimension Reduction. For different linear dimension reduction methods like principal components analysis (PCA), independent components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number of interesting components (ICs) are provided.

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References in zbMATH (referenced in 5 articles )

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  1. Klaus Nordhausen, Markus Matilainen, Jari Miettinen, Joni Virta, Sara Taskinen: Dimension Reduction for Time Series in a Blind Source Separation Context Using R (2021) not zbMATH
  2. Radojičić, Una; Nordhausen, Klaus; Virta, Joni: Large-sample properties of unsupervised estimation of the linear discriminant using projection pursuit (2021)
  3. Alexander Lange, Bernhard Dalheimer, Helmut Herwartz, Simone Maxand: svars: An R Package for Data-Driven Identification in Multivariate Time Series Analysis (2020) not zbMATH
  4. Radojičić, Una; Nordhausen, Klaus: Non-Gaussian component analysis: testing the dimension of the signal subspace (2020)
  5. Chen, Ding-Geng (Din); Peace, Karl E.; Zhang, Pinggao: Clinical trial data analysis using R and SAS (2017)