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Plot hierarchical moving-window statistical analysis for time series.

Source: R/TH_plotc.R
TH_plotc.Rd

Plots hierarchical moving-window statistical analysis for coupled time series. It returns analysis on moving correlations using Pearson's correlation coefficient and Mann-Kendall's correlation coefficient. The input is a data.frame created by TH_coupled() function.

Usage

TH_plotc(results, scale = NULL, output_file = NULL, mask = FALSE, mode = NULL)

Arguments

`results`

is a data.frame created by to TH_coupled().

`scale`

a numeric, scaling factor for point sizes, autoset by default.

`output_file`

is a string, optional, filename to save plot (NULL to skip saving).

`mask`

a logical value. If TRUE, shows significance in main plots and hides p-value plots for modes without explicit p-value requests. Only applicable for modes: "all", "kendall_with_p", and "pearson_with_p". For other modes, a warning is issued and mask is ignored.

`mode`

a character string specifying plots to show: "all", "pearson", "kendall", "both", "pearson_with_p", "kendall_with_p".

Value

A gridExtra arranged plot object.

Author

Vladimiro Andrea Boselli, (2025) boselli.v@irea.cnr.it

Examples

 if (FALSE) {
results <- TH_coupled(series1, series2, 4, 6)
TH_plotc(results, mask = TRUE, mode = "both")
TH_plotc(results, mode = "pearson_with_p")
}