Logical.
If FALSE do not bias correct variance, so plots have
appearance similar to Atkinson and Riani (2000).
If TRUE do bias correct variance, so plots start at origin.
Default is FALSE.
return
Logical. Default is FALSE: do not return values.
plot.legend
Logical. Default is TRUE: include legend in plot.
col
plot parameter. Vector of 6 colours.
legend
plot parameter. Vector of 6 characters.
lty
plot parameter. Vector of 6 line types.
lwd
plot parameter. Vector of 6 line widths.
main
plot parameter. Character.
type
plot parameter. Charcater for plot type.
xlab
plot parameter. Charcater for x label.
ylab
plot parameter. Charcater for y label.
Value
ref.dist
Character. From argument.
bias.correct
Logical. From argument.
forward.residual.scaled
Vector. Forward residuals scaled by estimated variance.
The estimated variance is or is not bias corrected depending on the choice of
bias.correct.
forward.asymp.median
Vector. Asymptotic median.
forward.asymp.sdv
Vector. Asymptotic standard deviation. Not divided by
squareroot of sample size.
cut.off
Matrix. Cut-offs taken from Table 3 of Johansen and Nielsen (2014).
Author(s)
Bent Nielsen <bent.nielsen@nuffield.ox.ac.uk> 9 Sep 2014
References
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.
Examples
#####################
# 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.plot(FS95)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(ForwardSearch)
Loading required package: robustbase
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ForwardSearch/ForwardSearch.plot.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ForwardSearch.plot
> ### Title: Plots forward residuals with simultaneous confidence bands
> ### Aliases: ForwardSearch.plot
>
> ### ** Examples
>
> #####################
> # 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.plot(FS95)
>
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.