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ForeComp

This repository contains the ForeComp R package for forecasting comparison and equal predictive accuracy testing. The package implements Diebold-Mariano and related procedures, including fixed-smoothing (fixed-b and fixed-m) variants, along with tools for size-power tradeoff analysis.

Contents

• R/ package source code implementing forecast evaluation functions
• data/ packaged datasets used by the package
• man/ function documentation (.Rd files)
• tests/testthat/ automated tests
• NEWS.md release notes and version history

The package code and datasets support forecasting-method comparison and robustness analysis for equal predictive accuracy testing.

Installation

ForeComp requires R (>= 3.5.0).

Install the stable release from CRAN:

install.packages("ForeComp")

Install the development version from GitHub:

remotes::install_github("mcmcs/ForeComp")

Main functions

Plot_Tradeoff(data, f1, f2, y, ...)

• Computes loss differentials between two forecast series and evaluates how the truncation choice (M) affects size distortion and maximum power loss.
• Fits an ARIMA approximation to the loss differential process and uses simulation (n_sim) to construct size-power tradeoff results across m_set.
• Returns a list where the first element is a ggplot2 tradeoff figure and the second element is the underlying computed table.

For direct equal-predictive-accuracy testing with specific bandwidth rules:

ForeComp supports both fixed-smoothing defaults and baseline alternatives for Bartlett-kernel DM tests:

• dm.test.bt(d, M = NA, Mopt = ...) (normal approximation, default Mopt = 2)
• dm.test.bt.fb(d, M = NA, Mopt = ...) (fixed-b approximation, default Mopt = 1)

For both functions, Mopt has the same meaning:

• Mopt = 1 (LLSW): M = ceiling(1.3 * sqrt(T))
• Mopt = 2 (NW 1994): M = ceiling(4 * (T / 100)^(2/9))
• Mopt = 3 (textbook NW / Andrews): M = ceiling(0.75 * T^(1/3))
• Mopt = 4 (CI baseline): M = floor(sqrt(T))

where T = length(d).

For EWC fixed-smoothing:

• dm.test.ewc.fb(d, B = NA, Bopt = 1) uses B = floor(0.4 * T^(2/3)) with a lower bound of 1.

Introductory Paper

Coming soon!

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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