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The functions provided in the FADA (Factor Adjusted Discriminant Analysis) package aim at performing supervised classification of high-dimensional and correlated profiles. The procedure combines a decorrelation step based on a factor modeling of the dependence among covariates and a classification method. The available methods are Lasso regularized logistic model (see Friedman et al. (2010)), sparse linear discriminant analysis (see Clemmensen et al. (2011)), shrinkage linear and diagonal discriminant analysis (see M. Ahdesmaki et al. (2010)). More methods of classification can be used on the decorrelated data provided by the package FADA.
● Data Source:
CranContrib
● Keywords:
● Alias: FADA-package
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decorrelate.test
(Package: FADA) :
Factor Adjusted Discriminant Analysis 2: Decorrelation of a testing data set after running the code{decorrelate.train
This function decorrelates the test dataset by adjusting data for the effects of latent factors of dependence, after running the decorrelate.train function on a training data set.
● Data Source:
CranContrib
● Keywords:
● Alias: decorrelate.test
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The test dataset has the same list structure as the training dataset dta. Only the numbers of rows of the x component and length of the y component are different since the test sample size is 1000.
● Data Source:
CranContrib
● Keywords:
● Alias: data.test
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FADA
(Package: FADA) :
Factor Adjusted Discriminant Analysis 3-4 : Supervised classification on decorrelated data
This function performs supervised classification on factor-adjusted data.
● Data Source:
CranContrib
● Keywords:
● Alias: FADA
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Simulated training dataset. The x component is a matrix of explanatory variables, with 30 rows and 250 columns. Each row is simulated according to a multinormal distribution which mean depends on a group membership given by the y component. The variance matrix is the same within each group.
● Data Source:
CranContrib
● Keywords:
● Alias: data.train
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decorrelate.train
(Package: FADA) :
Factor Adjusted Discriminant Analysis 1: Decorrelation of the training data
This function decorrelates the training dataset by adjusting data for the effects of latent factors of dependence.
● Data Source:
CranContrib
● Keywords:
● Alias: decorrelate.train
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providing 
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