wvar: Wavelet Variance

Description Usage Arguments Details Value Author(s) Examples

View source: R/wvar.R

Description

Calculates the (MO)DWT wavelet variance

Usage

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wvar(x, ...)

## S3 method for class 'lts'
wvar(
  x,
  decomp = "modwt",
  filter = "haar",
  nlevels = NULL,
  alpha = 0.05,
  robust = FALSE,
  eff = 0.6,
  to.unit = NULL,
  ...
)

## S3 method for class 'gts'
wvar(
  x,
  decomp = "modwt",
  filter = "haar",
  nlevels = NULL,
  alpha = 0.05,
  robust = FALSE,
  eff = 0.6,
  to.unit = NULL,
  ...
)

## S3 method for class 'ts'
wvar(
  x,
  decomp = "modwt",
  filter = "haar",
  nlevels = NULL,
  alpha = 0.05,
  robust = FALSE,
  eff = 0.6,
  to.unit = NULL,
  ...
)

## S3 method for class 'imu'
wvar(
  x,
  decomp = "modwt",
  filter = "haar",
  nlevels = NULL,
  alpha = 0.05,
  robust = FALSE,
  eff = 0.6,
  to.unit = NULL,
  ...
)

## Default S3 method:
wvar(
  x,
  decomp = "modwt",
  filter = "haar",
  nlevels = NULL,
  alpha = 0.05,
  robust = FALSE,
  eff = 0.6,
  freq = 1,
  from.unit = NULL,
  to.unit = NULL,
  ...
)

Arguments

x

A vector with dimensions N x 1.

...

Further arguments passed to or from other methods.

decomp

A string that indicates whether to use a "dwt" or "modwt" decomposition.

filter

A string that specifies which wavelet filter to use.

nlevels

An integer that indicates the level of decomposition. It must be less than or equal to floor(log2(length(x))).

alpha

A double that specifies the significance level which in turn specifies the 1-╬▒ confidence level.

robust

A boolean that triggers the use of the robust estimate.

eff

A double that indicates the efficiency as it relates to an MLE.

to.unit

A string indicating the unit to which the data is converted.

freq

A numeric that provides the rate of samples.

from.unit

A string indicating the unit from which the data is converted.

Details

The default value of nlevels will be set to floor(log2(length(x))), unless otherwise specified.

Value

A list with the structure:

Author(s)

James Balamuta, Justin Lee and Stephane Guerrier

Examples

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set.seed(999)
x = rnorm(100)

# Default
wvar(x)

# Robust
wvar(x, robust = TRUE, eff=0.3)

# Classical
wvar(x, robust = FALSE, eff=0.3)

# 90% Confidence Interval 
wvar(x, alpha = 0.10)

wv documentation built on Jan. 17, 2020, 1:07 a.m.

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