# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "cforecast" in publications use:' type: software license: GPL-3.0-or-later title: 'cforecast: Conditional Forecasting and Scenario Analysis Using VAR Models' version: 0.1.1 doi: 10.32614/CRAN.package.cforecast abstract: Provides tools for interpretable conditional forecasting and scenario analysis in reduced-form vector autoregressive (VAR) models. Implements a Kalman smoothing framework to generate forecasts under path restrictions on selected variables. The package enables decomposition of conditional forecasts into variable-specific contributions, and extraction of observation weights. It also computes measures of overall and marginal variable importance to enhance the economic interpretation of forecast revisions. The framework is structurally agnostic and suited for policy analysis, stress testing, and macro-financial applications. The methodology is described in more detail in Caspi and Ginker (2026) . authors: - family-names: Ginker given-names: Tim email: tim.ginker@gmail.com orcid: https://orcid.org/0000-0002-7138-5417 repository: https://timginker.r-universe.dev repository-code: https://github.com/timginker/cforecast commit: cf6bfac3d443994f7c3d90d13979850605e17bdc url: https://github.com/timginker/cforecast date-released: '2026-06-08' contact: - family-names: Ginker given-names: Tim email: tim.ginker@gmail.com orcid: https://orcid.org/0000-0002-7138-5417