wwntests: Hypothesis Tests for Functional Time Series

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.

Version:	1.1.0
Depends:	R (≥ 3.5.0)
Imports:	sde, stats, ftsa, rainbow, MASS, graphics, fda
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, CompQuadForm, tensorA
Published:	2023-12-01
DOI:	10.32614/CRAN.package.wwntests
Author:	Mihyun Kim [aut, cre], Daniel Petoukhov [aut]
Maintainer:	Mihyun Kim <mihyun.kim at mail.wvu.edu>
BugReports:	https://github.com/veritasmih/wwntests/issues
License:	GPL-3
NeedsCompilation:	no
Language:	en-US
Materials:	NEWS
CRAN checks:	wwntests results

Documentation:

Reference manual:	wwntests.pdf
Vignettes:	wwntests

Downloads:

Package source:	wwntests_1.1.0.tar.gz
Windows binaries:	r-devel: wwntests_1.1.0.zip, r-release: wwntests_1.1.0.zip, r-oldrel: wwntests_1.1.0.zip
macOS binaries:	r-release (arm64): wwntests_1.1.0.tgz, r-oldrel (arm64): wwntests_1.1.0.tgz, r-release (x86_64): wwntests_1.1.0.tgz, r-oldrel (x86_64): wwntests_1.1.0.tgz
Old sources:	wwntests archive

Linking:

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