dimJump.R {ClustMMDD} R Documentation

## Data driven calibration of the penalty function

### Description

Data driven calibration of the penalty function using the dimension jump version of the "slope heuristics".

### Usage

  dimJump.R(fileOrData, h = integer(), N = integer(), header = logical())


### Arguments

 fileOrData A character string or a data frame (see details). If a data frame, it must contain columns named logLik and dim. If a file, it must be as the one produced by backward.explorer. h An integer defining the size of the sliding window used to find the biggest jump. N The size of the sample data (number of rows). header The indication of whether the file contains header or not.

### Details

This function is a dimension jump version of the so called slope heuristics for the calibration of penalty function using the data.

### Value

Assume that the penalty function is in the form

pen≤ft(K,S\right) = α*λ*dim≤ft(K,S\right)

, where

• λ is the penalty parameter to be calibrated,

• and α a coeffcient belonging to [1.5,2], to be given by the user in model.selection.R for the final selection.

It returns a list containing two candidate values of λ and their bounds. It also produces a graphic that illustrates the "slope heuristics".

Wilson Toussile

### References

backward.explorer for exploration of competing models space, model.selection.R for final selection.
# genotype2_ExploredModels was obtained via backward.explorer.