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Last data update: 2014.03.03

R: Plot distribution of estimates

distribution.coefEstEval

R Documentation

Plot distribution of estimates

Description

Plot distribution of estimates.

Usage

     ## S3 method for class 'coefEstEval'
distribution(obj, ...,  Sort=FALSE, bandwidth=0.2,
	graphs.per.page=5)
     ## S3 method for class 'rootsEstEval'
distribution(obj, ..., mod=TRUE, invert=FALSE, Sort=FALSE,
        bandwidth=0.2, select=NULL)

Arguments

`obj`	an object as returned by EstEval.
`Sort`	if Sort is true then sort is applied. This helps (a bit) with estimation methods like black.box which may not return parameters of the same length or in the same order.
`bandwidth`	passed to `density` or `ksmooth`.
`graphs.per.page`	integer indicating number of graphs to place on a page.
`...`	other objects to be plotted (not working for some methods).
`invert`	logical indicating if the inverse of roots should be plotted
`mod`	logical indicating if the modulus of roots should be plotted
`select`	integer vector indicating roots to be plotted. If select is not NULL then roots are sorted by magnitude and only the indicated roots are plotted. For example, select=c(1,2) will plot only the two largest roots.

Details

ksmooth is applied if available to get a smoothed estimate of the distribution of the estimates. If ksmooth is not available then density is applied if it is available.

Value

None

Examples

data("eg1.DSE.data.diff", package="dse")
model <- estVARXls(TSdata(output=outputData(eg1.DSE.data.diff)), max.lag=2)
# now use this as the true model
z <-  EstEval(model, 
    estimation="estVARXls", estimation.args=list(max.lag=2))
distribution(z) 
tfplot(z)

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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> library(EvalEst)
Loading required package: tfplot
Loading required package: tframe
Loading required package: dse

Attaching package: 'dse'

The following objects are masked from 'package:stats':

    acf, simulate

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EvalEst/distribution.coefEstEval.Rd_%03d_medium.png", width=480, height=480)
> ### Name: distribution.coefEstEval
> ### Title: Plot distribution of estimates
> ### Aliases: distribution.coefEstEval distribution.rootsEstEval
> ### Keywords: ts
> 
> ### ** Examples
> 
> data("eg1.DSE.data.diff", package="dse")
> model <- estVARXls(TSdata(output=outputData(eg1.DSE.data.diff)), max.lag=2)
> # now use this as the true model
> z <-  EstEval(model, 
+     estimation="estVARXls", estimation.args=list(max.lag=2))
Calculating  100  estimates.
> distribution(z) 
> tfplot(z)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>