guidedModelSelection: Guided Model Selection

In DeCAFS: Detecting Changes in Autocorrelated and Fluctuating Signals

Guided Model Selection

Description

This function aids the user in selecting an appropriate model for a given sequence of observations. The function goes an interactive visualization of different model fits for different choices of initial parameter estimators and l0 penalties (beta). At the end, a call to the DeCAFS function is printed, while a DeCAFS wrapper is provvided.

Usage

guidedModelSelection(data)

Arguments

data	A vector of observations y

Value

A function, being a wrapper of DeCAFS with the selected parameter estimators.

Examples

## Not run: 
y <- dataRWAR(1000, sdEta = 1, sdNu = 4, phi = .4, nbSeg = 4, jumpSize = 20, type = "updown")$y
DeCAFSWrapper <- guidedModelSelection(y)

## End(Not run)

DeCAFS documentation built on Jan. 6, 2023, 5:27 p.m.