Changes in version 1.0.0 (2025-12-11)                  

  - Provides deterministic forecasting for weekly, monthly, quarterly,
    and yearly time series using the Generalized Adaptive Capped
    Estimator.

  - Includes a structured preprocessing pipeline with support for:
    
      - handling of non-positive or missing values,
      - optional interpolation,
      - optional winsorization of extreme observations.

  - Implements multiple growth components:
    
      - year-over-year,
      - short-term movement,
      - rolling-window behavior,
      - long-run drift.

  - Growth components are combined using a trimmed, robust averaging
    framework to ensure stable signal extraction across different series
    types.

  - Includes volatility-aware asymmetric caps that adapt to series
    characteristics and frequency.

  - Provides optional seasonal scaling using smoothed, normalized
    seasonal factors derived from the historical pattern.

  - Forecast generation uses a recursive formulation incorporating
    growth moderation (gamma) and level–growth blending (beta).

  - The user-facing function gace_forecast() returns forecasted values
    in a simple, consistent structure.

  - The helper function plot_gace() visualizes historical and projected
    values using ggplot2.

  - Package includes documentation, examples, vignette, tests, and is
    structured for CRAN compatibility.