R: Correlation Analysis Functions

corr_analysis {simts}

R Documentation

Correlation Analysis Functions

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

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

`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.

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

Yunxiang Zhang

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

[Package simts version 0.2.2 Index]