danigiro

FoReco

Forecast Reconciliation - Classical (bottom-up), optimal and heuristic combination forecast reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly constrained time series.

awesome-forecast-reconciliation

Collection of academic papers, articles, software tools, and educational resources about forecast reconciliation

ctprob

Cross-temporal probabilistic forecast reconciliation repository

f4sg_reconciliation

F4SG Learning Lab: Forecast Reconciliation for Hierarchically Organized Data

IJF_AUSGDP

Reconciliation of quarterly Australian GDP forecasts from Income and Expenditure sides

AusGDP_IJF

Australian Gross Domestic Product (GDP) application, Di Fonzo and Girolimetto (2021)

ct-comp

Insights into regression-based cross-temporal forecast reconciliation

FoCo2

Coherent Forecast Combination: multi-task forecast combination and reconciliation approaches leveraging input from multiple forecasting models or experts and ensuring that the resulting forecasts satisfy specified linear constraints.

mtsreco

Point and probabilistic forecast reconciliation for general linearly constrained multiple time series

SE_PV324

CranDownloads

A shiny app to check and compare package downloads from the CRAN

daniGiro

GitHub profile

forecast

forecast package for R

haR

R package to estimate and forecast the HAR (Heterogeneous Autoregressive) model and its extensions.

FoReco026

Docu: https://danigiro.github.io/FoReco026/ Warning: This package version is no longer supported. Please upgrade to FoReco 1.0 (https://danigiro.github.io/FoReco/), which includes significant changes and is not compatible with previous versions.

IJF_VN525

The monthly time series reconciliation of the Australian Tourism Flows disaggregated by geographic divisions and purpose of travel

phd-thesis

SS23project

tafs_reco

TimeGPTapi

Interface to interact with the TimeGPT API developed by Nixtla <https://nixtla.io/>. TimeGPT is a generative pre-trained transformer model specialized in prediction <https://docs.nixtla.io/docs>.