GitHub

Generalized Adaptive Capped Estimator
A stable, deterministic forecasting engine for weekly, monthly, quarterly, and yearly data.


Overview

GACE provides a transparent, tuning-free forecasting method based on hybrid growth signals and adaptive asymmetric caps.
It extends deterministic capped-growth forecasting to support weekly, monthly, quarterly, and yearly time series with optional seasonal scaling.

The method is designed for:

  • demand forecasting
  • operational forecasting
  • financial and portfolio forecasting
  • budgeting and scenario planning

The philosophy: Stable + Interpretable + Fast
No nonlinear optimization. No stochastic fitting. Fully deterministic.


Features

  • Supports weekly / monthly / quarterly / yearly data
  • Hybrid growth signals (year-over-year, short-term, rolling, drift)
  • Volatility-aware asymmetric caps
  • Seasonal and non-seasonal modes
  • Deterministic, extremely fast computation
  • plot_gace() for visualization
  • Lightweight dependencies

Installation

Install the released version from CRAN:

install.packages("GACE")

Example

library(GACE)
set.seed(1)
y <- ts(rnorm(60, mean = 100, sd = 10), frequency = 12)
fc <- gace_forecast(y, periods = 12, freq = "month")
plot_gace(fc)

Read the original on github.com ↗