seasonalMean, seasonalVar, seasonalACF {boodd}R Documentation

Computes time domain characteristics of periodically correlated time series

Description

Calculate estimates of the seasonal means, variances and autocovariances of a periodically correlated time series.

Usage

	seasonalMean(x,period,...)
	seasonalVar(x,period,...)
	seasonalACF(x,tau,period,...)

## Default S3 method:
seasonalMean(x,period,...)
## Default S3 method:
seasonalVar(x,period,...)
## Default S3 method:
seasonalACF(x,tau,period,...)

## S3 method for class 'ts'
seasonalMean(x,period=frequency(x),...)
## S3 method for class 'ts'
seasonalVar(x,period=frequency(x),...)
## S3 method for class 'ts'
seasonalACF(x,tau,period=frequency(x),...)

Arguments

x

A vector or time series representing a periodically correlated time series.

period

A positive integer; the period length. By default it is frequency(x).

tau

A vector of integers; a single lag or vector of lags.

...

Optional additional arguments for the function.

Details

The functions seasonalMean and seasonalVar calculate estimates of the seasonal means and variances respectively. The function seasonalACF calculates an estimator of the autocovariance for the given lags.

Value

The seasonalMean and seasonalVar functions return a vector of length period.

seasonalACF returns either a vector of length period if a single lag tau is specified, or a matrix with length(tau) rows and period columns if tau is a vector.

References

Bertail, P. and Dudek, A. (2025). Bootstrap for Dependent Data, with an R package (by Bernard Desgraupes and Karolina Marek) - submitted..

Hurd, H.L., Miamee, A.G. (2007). Periodically Correlated Random Sequences: Spectral. Theory and Practice. Wiley.

See Also

blockboot.seasonal, meanCoeff, acfCoeff, embb, embb.sample, bopt_circy.

Examples

# Means
seasonalMean(nottem)  # The period is already in the time-series object nottem
# Variances
seasonalVar(nottem)
# Autocovariances
seasonalACF(nottem,c(0,1))

[Package boodd version 0.1 Index]