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dLagM (version 1.0.2)

Time Series Regression Models with Distributed Lag Models

Description

Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Baltagi (2011) for more information.

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Version

Install

install.packages('dLagM')

Monthly Downloads

1,127

Version

1.0.2

License

GPL-3

Maintainer

Haydar Demirhan

Last Published

January 17th, 2018

Functions in dLagM (1.0.2)

dlm

Implement finite distributed lag model
dlmForecast

Compute forecasts for finite distributed lag model
MASE

Compute mean absolute scaled error (MASE) for distributed lag models
ardlDlm

Implement finite autoregressive distributed lag model
koyckDlmForecast

Compute forecasts for Koyck transformation of distributed lag models
polyDlm

Implement finite polynomial distributed lag model
finiteDLMauto

Find the optimal lag length for finite DLMs
koyckDlm

Implement distributed lag models with Koyck transformation
ardlDlmForecast

Compute forecasts for autoregressive distributed lag models
dLagM-package

Implementation of Time Series Regression Models with Distributed Lag Models
warming

Global warming and vehicle prediction data
polyDlmForecast

Compute forecasts for polynomial distributed lag model
sortScore

Sort ACI, BIC and MASE scores