FTSgof: White Noise and Goodness-of-Fit Tests for Functional Time Series
It offers comprehensive tools for the analysis of functional time series data, focusing on white noise hypothesis testing and goodness-of-fit evaluations, alongside functions for simulating data and advanced visualization techniques, such as 3D rainbow plots. These methods are described in Kokoszka, Rice, and Shang (2017) <doi:10.1016/j.jmva.2017.08.004>, Yeh, Rice, and Dubin (2023) <doi:10.1214/23-EJS2112>, Kim, Kokoszka, and Rice (2023) <doi:10.1214/23-ss143>, and Rice, Wirjanto, and Zhao (2020) <doi:10.1111/jtsa.12532>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | sde, graphics, stats,rgl,fda,nloptr,sfsmisc,MASS |
| Suggests: | knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2024-10-03 |
| DOI: | 10.32614/CRAN.package.FTSgof |
| Author: | Mihyun Kim [aut, cre], Chi-Kuang Yeh [aut], Yuqian Zhao [aut], Gregory Rice [ctb] |
| Maintainer: | Mihyun Kim <mihyun.kim at mail.wvu.edu> |
| BugReports: | https://github.com/veritasmih/FTSgof/issues |
| License: | GPL-3 |
| URL: | https://github.com/veritasmih/FTSgof |
| NeedsCompilation: | no |
| SystemRequirements: | XQuartz (https://www.xquartz.org/) |
| Language: | en-US |
| Materials: | README |
| CRAN checks: | FTSgof results |
Documentation:
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