corr_analysis: Correlation Analysis Functions

In SMAC-Group/simts: Time Series Analysis Tools

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.

Author(s)

Yunxiang Zhang

Examples

# Estimate both the ACF and PACF functions
corr_analysis(datasets::AirPassengers)

SMAC-Group/simts documentation built on Sept. 4, 2023, 5:25 a.m.