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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