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fDMA
View on CRAN: Click
here
Download and install fDMA package within the R console
Install from CRAN:
install.packages("fDMA")
Install from Github:
library("remotes")
install_github("cran/fDMA") Install by package version:
library("remotes")
install_version("fDMA", "2.2.9") Attach the package and use:
library("fDMA")
Maintained by
Krzysztof Drachal
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-07-10
Latest Update: 2025-01-24
Description:
Allows to estimate dynamic model averaging, dynamic model selection and median probability model. The original methods are implemented, as well as, selected further modifications of these methods. In particular the user might choose between recursive moment estimation and exponentially moving average for variance updating. Inclusion probabilities might be modified in a way using 'Google Trends'. The code is written in a way which minimises the computational burden (which is quite an obstacle for dynamic model averaging if many variables are used). For example, this package allows for parallel computations and Occam's window approach. The package is designed in a way that is hoped to be especially useful in economics and finance. Main reference: Raftery, A.E., Karny, M., Ettler, P. (2010) .
How to cite:
Krzysztof Drachal (2017). fDMA: Dynamic Model Averaging and Dynamic Model Selection for Continuous Outcomes. R package version 2.2.9, https://cran.r-project.org/web/packages/fDMA. Accessed 27 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:37), 1.0 (2017-07-10 00:50), 1.1 (2017-07-11 23:27), 2.0 (2017-08-31 10:05), 2.1 (2017-10-13 23:01), 2.2.1 (2017-11-24 14:03), 2.2.2 (2018-01-21 18:31), 2.2.3.1 (2018-06-29 14:51), 2.2.3 (2018-01-29 01:11), 2.2.4 (2018-09-30 00:00), 2.2.5 (2020-04-03 20:30), 2.2.6 (2020-07-17 11:20), 2.2.7 (2023-07-16 19:20), 2.2.8 (2025-01-24 11:00), 2.2 (2017-11-15 23:10)
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Other R packages that fDMA depends,
imports, suggests or enhances
Complete documentation for fDMA
Functions, R codes and Examples using
the fDMA R package
Some associated functions: altf . altf2 . altf3 . altf4 . archtest . coef.dma . crudeoil . descstat . dmtest . fDMA . fitted.dma . gNormalize . grid.DMA . grid.roll.reg . grid.tvp . hit.ratio . hmdmtest . mdmtest . normalize . onevar . plot.altf . plot.altf2 . plot.altf3 . plot.altf4 . plot.dma . plot.grid.dma . plot.grid.roll.reg . plot.grid.tvp . plot.reg . plot.tvp . predict.dma . print.altf . print.altf2 . print.altf3 . print.altf4 . print.dma . print.grid.dma . print.grid.roll.reg . print.grid.tvp . print.reg . print.tvp . rec.reg . reduce.size . residuals.dma . roll.reg . rvi . standardize . stest . summary.altf . summary.altf2 . summary.altf3 . summary.altf4 . summary.dma . summary.grid.dma . summary.grid.roll.reg . summary.grid.tvp . summary.reg . summary.tvp . trends . tvp .
Some associated R codes: RcppExports.R . altf.R . altf2.R . altf3.R . altf4.R . archtest.R . descstat.R . dmtest.R . fDMA.R . gNormalize.R . grid.DMA.R . grid.roll.reg.R . grid.tvp.R . hit.ratio.R . hmdmtest.R . mdmtest.R . normalize.R . onUnload.R . onevar.R . other.methods.dma.R . plot.altf.R . plot.altf2.R . plot.altf3.R . plot.altf4.R . plot.dma.R . plot.grid.dma.R . plot.grid.roll.reg.R . plot.grid.tvp.R . plot.reg.R . plot.tvp.R . print.altf.R . print.altf2.R . print.altf3.R . print.altf4.R . print.dma.R . print.grid.dma.R . print.grid.roll.reg.R . print.grid.tvp.R . print.reg.R . print.tvp.R . rec.reg.R . reduce.size.R . roll.reg.R . standardize.R . stest.R . summary.altf.R . summary.altf2.R . summary.altf3.R . summary.altf4.R . summary.dma.R . summary.grid.dma.R . summary.grid.roll.reg.R . summary.grid.tvp.R . summary.reg.R . summary.tvp.R . tvp.R . Full fDMA package functions and examples
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