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correl_plots

Source: R/correl_plots.R
correl_plots.Rd

Computes bivariate correlation diagnostics for two xts timeseries. The function produces a three-panel plot consisting of a scatter plot annotated with the Pearson correlation coefficient, an empirical copula plot annotated with the Spearman correlation coefficient, and a standard-normal semi-correlation plot that decomposes the joint dependence into four quadrant-specific correlations. Missing values are handled via casewise deletion, and zero values below a supplied threshold may optionally be filtered before computation. When check_common = TRUE, only dates common to both series are retained, ensuring paired comparisons on synchronised indices. The panels are assembled via patchwork::wrap_plots and returned as a list alongside the individual ggplot objects and a correlation table.

Usage

correl_plots(
  x,
  y,
  check_common = TRUE,
  ignore_zeros = FALSE,
  zero_threshold = 0.01
)

Arguments

x, y

xts objects containing the time series data.

check_common

Logical. If TRUE (default), only dates present in both series are used.

ignore_zeros

Logical. If TRUE, values below zero_threshold are excluded. Default FALSE.

zero_threshold

Numeric. Threshold below which values are treated as zero. Default 0.01.

Value

A list with elements combined (patchwork of the three panels), scatter_plot, copula_plot, normal_plot (individual ggplot objects), and correl_table (matrix of Pearson, Spearman, and four semi-correlation coefficients).

Examples

x <- xts::xts(rnorm(365), order.by = as.Date("2020-01-01") + 0:364)
y <- xts::xts(rnorm(365), order.by = as.Date("2020-01-01") + 0:364)
correls <- correl_plots(x, y, check_common = TRUE)
correls$combined
#> Ignoring unknown labels:
#> • colour : "Case"
#> Ignoring unknown labels:
#> • colour : "Case"
#> Ignoring unknown labels:
#> • colour : "Case"
#> Warning: Removed 10 rows containing missing values or values outside the scale range
#> (`geom_line()`).
#> Warning: Removed 10 rows containing missing values or values outside the scale range
#> (`geom_line()`).