Simca-class function

Class "Simca" - virtual base class for all classic and robust SIMCA classes representing classification in high dimensions based on the SIMCA method

The class Simca searves as a base class for deriving all other classes representing the results of the classical and robust SIMCA methods 1.1

class

Objects from the Class

A virtual Class: No objects may be created from it.

Slots

• call:: the (matched) function call.
• prior:: prior probabilities used, default to group proportions
• counts:: number of observations in each class
• pcaobj:: A list of Pca objects - one for each group
• k:: Object of class "numeric" number of (choosen) principal components
• flag:: Object of class "Uvector" The observations whose score distance is larger than cutoff.sd or whose orthogonal distance is larger than cutoff.od can be considered as outliers and receive a flag equal to zero. The regular observations receive a flag 1
• X:: the training data set (same as the input parameter x of the constructor function)
• grp:: grouping variable: a factor specifying the class for each observation.

Methods

• predict: signature(object = "Simca"): calculates prediction using the results in object. An optional data frame or matrix in which to look for variables with which to predict. If omitted, the training data set is used. If the original fit used a formula or a data frame or a matrix with column names, newdata must contain columns with the same names. Otherwise it must contain the same number of columns, to be used in the same order.
• show: signature(object = "Simca"): prints the results
• summary: signature(object = "Simca"): prints summary information

References

Vanden Branden K, Hubert M (2005) Robust classification in high dimensions based on the SIMCA method. Chemometrics and Intellegent Laboratory Systems 79:10--21

Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32 (3), 1--47, tools:::Rd_expr_doi("10.18637/jss.v032.i03") .

Todorov V & Filzmoser P (2014), Software Tools for Robust Analysis of High-Dimensional Data. Austrian Journal of Statistics, 43 (4), 255--266, tools:::Rd_expr_doi("10.17713/ajs.v43i4.44") .

Author(s)

Valentin Todorov valentin.todorov@chello.at

Examples

showClass("Simca")