Package: uotm 0.1.6

uotm: Uncertainty of Time Series Model Selection Methods

We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance not pay attention to the accuracy of prediction, but focus on model selection uncertainty and providing more information of the model selection results. And to estimate the model measures, we propose an simplify and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. We propose a new procedure, called model uncertainty variance, which can quantify the uncertainty of model selection on Autoregressive Moving Average models. The model uncertainty variance focuses on model selection uncertainty and providing more information of the model selection results. To estimate the model uncertainty variance, we propose an simplified and faster algorithm based on bootstrap method, which is proven to be effective and feasible by Monte-Carlo simulation. At the same time, we also made some optimizations and adjustments to the Model Confidence Bounds algorithm, so that it can be applied to the time series model selection method. The consistency of the algorithm result is also verified by Monte-Carlo simulation. Please see Li,Y., Luo,Y., Ferrari,D., Hu,X. and Qin,Y. (2019) Model Confidence Bounds for Variable Selection. Biometrics, 75:392-403.<doi:10.1111/biom.13024> for more information.

Authors:Heming Deng Developer [aut, cre, cph], Sunan Gao Dev [aut]

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# Install 'uotm' in R:
install.packages('uotm', repos = c('https://heming0425.r-universe.dev', 'https://cloud.r-project.org'))

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This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5 exports 0.00 score 47 dependencies 4 scripts 165 downloads

Last updated 2 years agofrom:1b16055a84. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 30 2024
R-4.5-winOKAug 30 2024
R-4.5-linuxOKAug 30 2024
R-4.4-winOKAug 30 2024
R-4.4-macOKAug 30 2024
R-4.3-winOKAug 30 2024
R-4.3-macOKAug 30 2024

Exports:arma.mcbarma.mucarma.muvarma.plotarma.sim

Dependencies:bootclicolorspacecurlfansifarverforecastfracdiffgenericsggplot2gluegtablehashisobandjsonlitelabelinglatticelifecyclelmtestmagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigquadprogquantmodR6RColorBrewerRcppRcppArmadillorlangscalestibbletimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo