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 | 
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