White Noise and Goodness-of-Fit Tests for Functional Time Series
FAR(p) Data Generator
Functional ARCH/GARCH Process Generator
Ornstein–Uhlenbeck Process Generator
Test based on fACF
Functional Autocorrelation Function (fACF) Plot
Test for Conditional Heteroscedasticity of Functional Time Series
Exploratory Data Analysis for Functional Time Series.
Goodness-of-fit Tests for Functional Times Series
White Noise Hypothesis Tests for Functional Times Series
Test based on fSACF
Functional Spherical Autocorrelation Function (fSACF) Plot
Goodness-of-fit test for FAR(1)
Goodness-of-fit Test for Functional ARCH/GARCH Model
Convert Original Price Data to OCIDRs
3D Rainbow Plot 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>.