simts (version 0.1.1)

corr_analysis: Correlation Analysis Functions

Description

Correlation Analysis function computes and plots both empirical ACF and PACF of univariate time series.

Usage

corr_analysis(x, lag.max = NULL, type = "correlation", demean = TRUE,
  show.ci = TRUE, alpha = 0.05, plot = TRUE, ...)

Arguments

x

A vector or "ts" object (of length \(N > 1\)).

lag.max

A integer indicating the maximum lag up to which to compute the ACF and PACF functions.

type

A character string giving the type of acf to be computed. Allowed values are "correlation" (the default) and "covariance".

demean

A bool indicating whether the data should be detrended (TRUE) or not (FALSE). Defaults to TRUE.

show.ci

A bool indicating whether to compute and show the confidence region. Defaults to TRUE.

alpha

A double indicating the level of significance for the confidence interval. By default alpha = 0.05 which gives a 1 - alpha = 0.95 confidence interval.

plot

A bool indicating whether a plot of the computed quantities should be produced. Defaults to TRUE.

...

Additional parameters.

Value

Two array objects (ACF and PACF) of dimension \(N \times S \times S\).

Examples

# NOT RUN {
# Estimate both the ACF and PACF functions
corr_analysis(datasets::AirPassengers)
# }