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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling source/ R- | FTSgof_1.0.0.tar.gz |
436.7 KiB |
1.0.0 |
rolling linux/jammy R-4.5 | FTSgof_1.0.0.tar.gz |
579.2 KiB |
1.0.0 |
latest source/ R- | FTSgof_1.0.0.tar.gz |
436.7 KiB |
1.0.0 |
latest linux/jammy R-4.5 | FTSgof_1.0.0.tar.gz |
579.2 KiB |
1.0.0 |
2026-04-23 source/ R- | FTSgof_1.0.0.tar.gz |
436.7 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | FTSgof_1.0.0.zip |
574.8 KiB |
1.0.0 |
2025-04-20 source/ R- | FTSgof_1.0.0.tar.gz |
436.7 KiB |