White Noise and Goodness-of-Fit Tests for Functional Time Series R package FTSgof version 1.0.0 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>. Software Depends: R (>= 3.5.0) Imports: sde, graphics, stats, rgl, fda, nloptr, sfsmisc, MASS Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Mihyun Kim <mihyun.kim@mail.wvu.edu> Comprehensive R Archive Network (CRAN) Mihyun Kim [aut, cre], Chi-Kuang Yeh [aut] (ORCID: <https://orcid.org/0000-0001-7057-2096>), Yuqian Zhao [aut], Gregory Rice [ctb] GPL-3 2024-10-03 application/tgz https://CRAN.R-project.org/package=FTSgof doi:10.32614/CRAN.package.FTSgof en-US