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url: https://taf-society.github.io/caretForecast/
template:
bootstrap: 5
bslib:
# TAF Society theme (matching Durbyn.jl)
bg: "#ffffff"
fg: "#0b1324"
primary: "#2e7dd7"
secondary: "#6b7280"
base_font:
google: "Inter"
code_font:
google: "JetBrains Mono"
border-radius: 0.75rem
btn-border-radius: 0.75rem
card-bg: "#f8fafc"
home:
title: caretForecast
description: Conformal Time Series Forecasting Using Machine Learning
sidebar:
structure: [links, license, community, citation, authors, toc, dev]
links:
- text: Report a bug
href: https://github.com/taf-society/caretForecast/issues
- text: TAFS Website
href: https://taf-society.org/
navbar:
structure:
left: [intro, reference, articles, news]
right: [search, github]
components:
github:
icon: fab fa-github
href: https://github.com/taf-society/caretForecast
aria-label: GitHub
reference:
- title: Model Fitting
desc: >
Functions for fitting machine learning models to time series data.
contents:
- ARml
- suggested_methods
- title: Forecasting
desc: >
Generate point forecasts and prediction intervals.
contents:
- forecast.ARml
- title: Conformal Prediction
desc: >
Functions for computing conformal prediction intervals with proper
coverage guarantees.
contents:
- conformalRegressor
- conformalRegressorByHorizon
- predict.conformalRegressor
- predict.conformalRegressorByHorizon
- title: Model Diagnostics
desc: >
Tools for evaluating and understanding model performance.
contents:
- get_var_imp
- title: Data Utilities
desc: >
Helper functions for preparing time series data.
contents:
- split_ts
- title: Datasets
desc: >
Example datasets included in the package.
contents:
- retail
- retail_wide
- title: Re-exports
desc: >
Functions re-exported from other packages for convenience.
contents:
- reexports
authors:
Resul Akay:
href: https://github.com/taf-society
footer:
structure:
left: tafs
right: built_with
components:
tafs: "Developed by [Time Series Analysis and Forecasting Society](https://taf-society.org/)"