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wwntests  

Hypothesis Tests for Functional Time Series
View on CRAN: Click here


Download and install wwntests package within the R console
Install from CRAN:
install.packages("wwntests")

Install from Github:
library("remotes")
install_github("cran/wwntests")

Install by package version:
library("remotes")
install_version("wwntests", "1.1.0")



Attach the package and use:
library("wwntests")
Maintained by
Mihyun Kim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-06-19
Latest Update: 2023-12-01
Description:
Provides a collection of white noise hypothesis tests for functional time series and related visualizations. These include tests based on the norms of autocovariance operators that are built under both strong and weak white noise assumptions. Additionally, tests based on the spectral density operator and on principal component dimensional reduction are included, which are built under strong white noise assumptions. Also, this package provides goodness-of-fit tests for functional autoregressive of order 1 models. These methods are described in Kokoszka et al. (2017) <doi:10.1016/j.jmva.2017.08.004>, Characiejus and Rice (2019) <doi:10.1016/j.ecosta.2019.01.003>, Gabrys and Kokoszka (2007) <doi:10.1198/016214507000001111>, and Kim et al. (2023) <doi:10.1214/23-SS143> respectively.
How to cite:
Mihyun Kim (2019). wwntests: Hypothesis Tests for Functional Time Series. R package version 1.1.0, https://cran.r-project.org/web/packages/wwntests. Accessed 27 Jan. 2025.
Previous versions and publish date:
1.0.0 (2019-06-19 12:50), 1.0.1 (2020-05-18 22:10), 1.0.2 (2022-11-01 16:10)
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