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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "autoann" in publications use:'
type: software
license: GPL-3.0-only
title: 'autoann: Neural Network–Based Model Selection and Forecasting'
version: 0.1.0
doi: 10.32614/CRAN.package.autoann
abstract: Provides a systematic framework for neural network–based model selection
  and forecasting using single hidden layer feed-forward networks. It evaluates all
  possible combinations of predictor variables and hidden layer configurations, selecting
  the optimal model based on predictive accuracy criteria such as root mean squared
  error (RMSE) and mean absolute percentage error (MAPE). Predictors are automatically
  standardized, and model performance is assessed using out-of-sample validation.
  The package is designed for empirical modelling and forecasting in economics, agriculture,
  trade, climate, and related applied research domains where nonlinear relationships
  and robust predictive performance are of primary interest.
authors:
- family-names: Pandit
  given-names: Dr. Pramit
  email: pramitpandit@gmail.com
- family-names: Paul
  given-names: Ms. Moumita
- family-names: Ghose
  given-names: Dr. Bikramjeet
repository: https://cran.r-universe.dev
commit: 4fff3bd3f62efee1fff2032e49eec9397449a47a
date-released: '2026-01-15'
contact:
- family-names: Pandit
  given-names: Dr. Pramit
  email: pramitpandit@gmail.com