Package: InterNL Type: Package Title: Time Series Intervention Model Using Non-Linear Function Version: 0.1.0 Authors@R: c(person("Dr. Amrit Kumar", "Paul", role = "aut"), person("Dr. Md", "Yeasin", role = c("aut","cre"), email = "yeasin.iasri@gmail.com"), person("Dr. Ranjit Kumar", "Paul", role = "aut"), person("Mr. Subhankar", "Biswas", role = "aut"), person("Dr. HS", "Roy", role = "aut"), person("Dr. Prakash", "Kumar", role = "aut") ) Author: Dr. Amrit Kumar Paul [aut], Dr. Md Yeasin [aut, cre], Dr. Ranjit Kumar Paul [aut], Mr. Subhankar Biswas [aut], Dr. HS Roy [aut], Dr. Prakash Kumar [aut] Maintainer: Dr. Md Yeasin Description: Intervention analysis is used to investigate structural changes in data resulting from external events. Traditional time series intervention models, viz. Autoregressive Integrated Moving Average model with exogeneous variables (ARIMA-X) and Artificial Neural Networks with exogeneous variables (ANN-X), rely on linear intervention functions such as step or ramp functions, or their combinations. In this package, the Gompertz, Logistic, Monomolecular, Richard and Hoerl function have been used as non-linear intervention function. The equation of the above models are represented as: Gompertz: A * exp(-B * exp(-k * t)); Logistic: K / (1 + ((K - N0) / N0) * exp(-r * t)); Monomolecular: A * exp(-k * t); Richard: A + (K - A) / (1 + exp(-B * (C - t)))^(1/beta) and Hoerl: a*(b^t)*(t^c).This package introduced algorithm for time series intervention analysis employing ARIMA and ANN models with a non-linear intervention function. This package has been developed using algorithm of Yeasin et al. and Paul and Yeasin . License: GPL-3 Encoding: UTF-8 Imports: stats, forecast, MLmetrics RoxygenNote: 7.2.1 NeedsCompilation: no Packaged: 2026-10-08 09:37:39 UTC; root Repository: https://yeasinstat.r-universe.dev Date/Publication: 2024-04-19 02:34:51 UTC RemoteUrl: https://github.com/cran/InterNL RemoteRef: HEAD RemoteSha: 902b4fd2850b9ae8a8d6406529e12b21243d1a5b