Plot Comparison of HP vs Modified HP

Create a ggplot2 comparison of HP and Modified HP filter trends. Useful for visualizing differences between fixed and optimized smoothing.

Usage

plot_comparison(
  x,
  frequency = c("quarterly", "annual"),
  max_lambda = 100000L,
  show_cycle = FALSE
)

Arguments

x

Numeric vector. The time series.

frequency

Character. Data frequency: "quarterly" or "annual".

max_lambda

Integer. Maximum lambda for Modified HP search.

show_cycle

Logical. If TRUE, also show cyclical components.

Value

A ggplot object.

Details

Creates comparison plots showing: 1. Original series with HP and Modified HP trends overlaid 2. (Optional) Cyclical components from both methods

The plot uses distinct colors and line styles to differentiate methods, with annotations showing lambda values.

Examples

set.seed(123)
# Simulate realistic economic data
n <- 100
base_level <- 100
growth_rate <- 0.5
volatility <- 1.2

y <- base_level + cumsum(rnorm(n, mean = growth_rate / 100, sd = volatility / 100)) +
  2.5 * sin(2 * pi * (1:n) / 25) + rnorm(n, sd = 0.5)

if (require(ggplot2)) {
  # Basic comparison
  plot_comparison(y, frequency = "quarterly", max_lambda = 10000)

  # With cycles
  plot_comparison(y, frequency = "quarterly", max_lambda = 10000, show_cycle = TRUE)

  # Customized plot
  p <- plot_comparison(y, frequency = "quarterly", max_lambda = 10000)
  p <- p +
    ggplot2::labs(
      title = "HP vs Modified HP: Trend Comparison",
      subtitle = "Quarterly macroeconomic series"
    ) +
    ggplot2::theme(
      plot.title = ggplot2::element_text(face = "bold", size = 14),
      legend.title = ggplot2::element_blank(),
      legend.position = "bottom"
    )
  print(p)
}