wavFDP: Class constructor for block- and time-dependent wavelet-based...

Description Usage Arguments S3 METHODS See Also Examples

Description

Class constructor for block- and time-dependent wavelet-based FD model parameter estimators.

Usage

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wavFDP(estimator, delta, variance.delta,
    innovations.variance, delta.range, dictionary, levels,
    edof.mode, boundary, series, sdf.method, type)

Arguments

estimator

character string briefly describing the estimator.

delta

numeric value/vector denoting the estimated FD model parameter.

innovations.variance

numeric value/vector denoting the estimated FD innovations variance.

variance.delta

numeric value/vector defining the variance of delta.

delta.range

two element numeric vector defining the range of delta.

dictionary

wavelet transform dictionary used in the analysis.

levels

vector of integers denoting the wavelet decomposition levels used in the analysis.

edof.mode

an integer on [1,3] defining the equivalent degrees of freedom mode used in the analysis.

boundary

a list containing named objects mode and description, containing a logical value and a character string, respectively. The mode object should be be TRUE if a boundary treatment was used, and description should contain a description of the boundary treatment.

series

a signSeries object containing the input series.

sdf.method

a character string defining the SDF method used in the analysis, e.g., "Integration lookup table".

type

a character string defining the type of estimator, e.g., ""instantaneous"" or "block".

S3 METHODS

eda.plot

extended data analyis plot of the data. Available options are:

mean.delta

mean value of delta, plotted as a horizontal reference line for instantaneous delat estimations. Default: NULL (no reference line).

xlab

character string defining the x-axis label. Default: "Time".

ylab

character string defining the y-axis label. Default: biased/unbiased and estimator condition.

title.str

character string defining the main title of the plot. Default: NULL (no title).

type

character string defining type of plot ala par function. Default: "l" (solid line).

plot

plots a summary of the results. Available options are:

mean.delta

mean value of delta, plotted as a horizontal reference line for instantaneous delat estimations. Default: NULL (no reference line).

xlab

character string defining the x-axis label. Default: "Time".

ylab

character string defining the y-axis label. Default: biased/unbiased and estimator condition.

title.str

character string defining the main title of the plot. Default: NULL (no title).

type

character string defining type of plot ala par function. Default: "l" (solid line).

show.key

a logical value. If TRUE, a key of the plot is shown. Default: TRUE.

conf.color

color index ala par for the confidence intervals. Default: 16.

print

prints the object. Available options are:

digits

number of digits to use in displaying numeric values. Default: 5.

print.summary

print a summary of the results.

summary

create a summary of the results.

See Also

wavFDPBlock, wavFDPTime.

Examples

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## create a faux dictionary 
dictionary <- wavDictionary(wavelet="s8",
    dual=FALSE, decimate=FALSE, n.sample=512,
    attr.x=NULL, n.levels=5,
    boundary="periodic", conv=TRUE,
    filters=wavDaubechies("s8"),
    fast=TRUE, is.complex=FALSE)

## construct a faux wavFDP object 
z <- wavFDP(estimator="wlse",
    delta=0.45,
    variance.delta=1.0,
    innovations.variance=1.0,
    delta.range=c(-10.0,10.0),
    dictionary=dictionary,
    levels=c(1,3:4),
    edof.mode=2,
    boundary=list(mode=TRUE,description="unbiased"),
    series=create.signalSeries(fdp045),
    sdf.method="Integration lookup table",
    type="block")

## print the result 
print(z)

Example output

Block-dependent FD parameter estimation 
----------------------------------------
FD parameter estimate (delta) : 0.45 
var{delta} estimate           : 1 
Innovations variance estimate : NA 
Estimator                     : WLSE 
Levels                        : 1 3 4 
Boundary mode                 : unbiased 
EDOF mode                     : 2 
Delta range                   : -10 10 
Wavelet                       : s8 
Length of series              : 512 
Number of levels              : 5 
Boundary correction rule      : periodic 
Filtering technique           : Convolution 

wmtsa documentation built on May 2, 2019, 6:50 p.m.

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