ForwardSearch.stopped: Forward estimators after m steps
In ForwardSearch: Forward Search using asymptotic theory

Description Usage Arguments Value Author(s) References Examples

A Forward Search gives a sequence of regression estimators. This function gives the regression estimators when stopped at m.

1	ForwardSearch.stopped(FS, m)

`FS`	List. Value of the function `ForwardSearch.fit`.
`m`	Integer. Stopping time.

`ranks.selected`	Vector. Ranks of m observations in the selected set.
`ranks.outliers`	Vector. Ranks of n-m observations that are not selected. These are the "outliers". It is the complement to `ranks.selected`.
`beta.m`	Vector. Least squares estimator based on `ranks.selected`.
`sigma2.biased Scalar.`	Scalar. Least squares residual variance based on `ranks.selected`. Value is not bias corrected.

Bent Nielsen <bent.nielsen@nuffield.ox.ac.uk> 9 Sep 2014

Johansen, S. and Nielsen, B. (2013) Asymptotic analysis of the Forward Search. Download: Nuffield DP.

Johansen, S. and Nielsen, B. (2014) Outlier detection algorithms for least squares time series. Download: Nuffield DP.

#####################
#	EXAMPLE 1
#	using Fulton Fish data,
#	see Johansen and Nielsen (2014).

#	Call package
library(ForwardSearch)

#	Call data
data(Fulton)
mdata	<- as.matrix(Fulton)
n		<- nrow(mdata)

#	Identify variable to reproduce Johansen and Nielsen (2014)
q		<- mdata[2:n		,9]
q_1		<- mdata[1:(n-1) ,9]
s		<- mdata[2:n		,6]
x.q.s	<- cbind(q_1,s)
colnames(x.q.s	)	<- c("q_1","stormy")

#	Fit Forward Search
FS95	<- ForwardSearch.fit(x.q.s,q,psi.0=0.95)

ForwardSearch.stopped(FS95,107)