ccf_plot: Time Series Cross Correlation Lags Visualization

In TSstudio: Functions for Time Series Analysis and Forecasting

Time Series Cross Correlation Lags Visualization

Description

Visualize the series y against the series x lags (according to the setting of the lags argument) and return the corresponding cross-correlation value for each lag

Usage

ccf_plot(x, y, lags = 0:12, margin = 0.02, n_plots = 3,
  Xshare = TRUE, Yshare = TRUE, title = NULL)

Arguments

x	A univariate time series object of a class "ts"
y	A univariate time series object of a class "ts"
lags	An integer, set the lags range, by default will plot the two series along with the first 12 lags
margin	Plotly parameter, either a single value or four values (all between 0 and 1). If four values provided, the first will be used as the left margin, the second will be used as the right margin, the third will be used as the top margin, and the fourth will be used as the bottom margin. If a single value provided, it will be used as all four margins.
n_plots	An integer, define the number of plots per row
Xshare	Plotly parameter, should the x-axis be shared amongst the subplots?
Yshare	Plotly parameter, should the y-axis be shared amongst the subplots?
title	A character, optional, set the plot title

Value

Plot

Examples

data("USUnRate")
data("USVSales")

ccf_plot(x = USVSales, y = USUnRate)

#Plotting the first 6 lead and lags of the USVSales with the USUnRate
ccf_plot(x = USVSales, y = USUnRate, lags = -6:6)

# Setting the plot margin and number of plots in each raw
ccf_plot(x = USVSales, y = USUnRate, lags = c(0, 6, 12, 24), 
margin = 0.01,  n_plots = 2)

TSstudio documentation built on Aug. 9, 2023, 9:06 a.m.