smooth

Forecasting Using State Space Models

Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes Exponential Smoothing, SARIMA, Complex Exponential Smoothing, Simple Moving Average, Vector Exponential Smoothing in state space forms, several simulation functions and intermittent demand state space models.

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Description file content

Package
smooth
Type
Package
Title
Forecasting Using State Space Models
Version
2.4.5
Date
2018-07-03
URL
BugReports
https://github.com/config-i1/smooth/issues
Description
Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes Exponential Smoothing, SARIMA, Complex Exponential Smoothing, Simple Moving Average, Vector Exponential Smoothing in state space forms, several simulation functions and intermittent demand state space models.
License
GPL (>= 2)
Depends
R (>= 3.0.2), greybox (>= 0.2.2)
Imports
Rcpp (>= 0.12.3), stats, graphics, forecast, nloptr, utils, zoo
LinkingTo
Rcpp, RcppArmadillo (>= 0.8.100.0.0)
Suggests
Mcomp, numDeriv, testthat, knitr, rmarkdown
VignetteBuilder
knitr
RoxygenNote
6.0.1
NeedsCompilation
yes
Packaged
2018-07-03 17:25:12 UTC; config
Author
Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer
Ivan Svetunkov
Repository
CRAN
Date/Publication
2018-07-03 18:20:03 UTC

install.packages('smooth')

2.4.5

a month ago

https://github.com/config-i1/smooth

Ivan Svetunkov

GPL (>= 2)

Depends on

R (>= 3.0.2), greybox (>= 0.2.2)

Imports

Rcpp (>= 0.12.3), stats, graphics, forecast, nloptr, utils, zoo

Suggests

Mcomp, numDeriv, testthat, knitr, rmarkdown

Discussions