corr_analysis: Correlation Analysis Functions

Description Usage Arguments Value Author(s) Examples

View source: R/ACF.R

Description

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

Usage

1
2
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 x S x S.

Author(s)

Yunxiang Zhang

Examples

1
2
# Estimate both the ACF and PACF functions
corr_analysis(datasets::AirPassengers)

SMAC-Group/simts documentation built on Nov. 11, 2018, 2:02 a.m.