Package: fdaoutlier 0.2.1

fdaoutlier: Outlier Detection Tools for Functional Data Analysis

A collection of functions for outlier detection in functional data analysis. Methods implemented include directional outlyingness by Dai and Genton (2019) <doi:10.1016/j.csda.2018.03.017>, MS-plot by Dai and Genton (2018) <doi:10.1080/10618600.2018.1473781>, total variation depth and modified shape similarity index by Huang and Sun (2019) <doi:10.1080/00401706.2019.1574241>, and sequential transformations by Dai et al. (2020) <doi:10.1016/j.csda.2020.106960 among others. Additional outlier detection tools and depths for functional data like functional boxplot, (modified) band depth etc., are also available.

Authors:Oluwasegun Taiwo Ojo [aut, cre, cph], Rosa Elvira Lillo [aut], Antonio Fernandez Anta [aut, fnd]

fdaoutlier_0.2.1.tar.gz
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fdaoutlier_0.2.1.tgz(r-4.6-x86_64)fdaoutlier_0.2.1.tgz(r-4.6-arm64)fdaoutlier_0.2.1.tgz(r-4.5-x86_64)fdaoutlier_0.2.1.tgz(r-4.5-arm64)
fdaoutlier_0.2.1.tar.gz(r-4.7-arm64)fdaoutlier_0.2.1.tar.gz(r-4.7-x86_64)fdaoutlier_0.2.1.tar.gz(r-4.6-arm64)fdaoutlier_0.2.1.tar.gz(r-4.6-x86_64)
fdaoutlier_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fdaoutlier/json (API)

# Install 'fdaoutlier' in R:

install.packages('fdaoutlier', repos = c('https://otsegun.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/otsegun/fdaoutlier/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

spanish_weather - Spanish Weather Data
world_population - World Population Data by Countries

On CRAN:

outlier-detection cpp

5.64 score 5 stars 1 packages 58 scripts 372 downloads 24 exports 1 dependencies

Last updated from:c96c35b1a7. Checks:11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	158
linux-devel-x86_64	NOTE	179
source / vignettes	OK	187
linux-release-arm64	NOTE	173
linux-release-x86_64	NOTE	168
macos-release-arm64	NOTE	122
macos-release-x86_64	NOTE	228
macos-oldrel-arm64	NOTE	136
macos-oldrel-x86_64	NOTE	276
windows-devel	NOTE	89
windows-release	NOTE	130
windows-oldrel	NOTE	152
wasm-release	OK	124

Exports:band_depth dir_out directional_quantile extremal_depth extreme_rank_length functional_boxplot linfinity_depth modified_band_depth msplot muod projection_depth seq_transform simulation_model1 simulation_model2 simulation_model3 simulation_model4 simulation_model5 simulation_model6 simulation_model7 simulation_model8 simulation_model9 total_variation_depth tvd_mss tvdmss

Dependencies:MASS

Simulation Models

Rendered fromsimulation_models.Rmdusingknitr::rmarkdown

Last update: 2021-03-01
Started: 2021-03-01

Help page	Topics
Compute the band depth for a sample of curves/observations.	band_depth
Dai & Genton (2019) Directional outlyingness for univariate or multivariate functional data.	dir_out
Compute directional quantile outlyingness for a sample of discretely observed curves	directional_quantile
Compute extremal depth for functional data	extremal_depth
Compute the Extreme Rank Length Depth.	extreme_rank_length
Functional Boxplot for a sample of functions.	functional_boxplot
Compute F distribution factors for approximating the tail of the distribution of robust MCD distance.	hardin_factor_numeric
Compute the L-infinity depth of a sample of curves/functions.	linfinity_depth
Compute the modified band depth for a sample of curves/functions.	modified_band_depth
Outlier Detection using Magnitude-Shape Plot (MS-Plot) based on the directional outlyingness for functional data.	msplot
Massive Unsupervised Outlier Detection (MUOD)	muod
Plot Data from simulation models	plot_dtt
Random projection for multivariate data	projection_depth
Find and classify outliers functional outliers using Sequential Transformation	seq_transform
Convenience function for generating functional data	simulation_model1
Convenience function for generating functional data	simulation_model2
Convenience function for generating functional data	simulation_model3
Convenience function for generating functional data	simulation_model4
Convenience function for generating functional data	simulation_model5
Convenience function for generating functional data	simulation_model6
Convenience function for generating functional data	simulation_model7
Convenience function for generating functional data	simulation_model8
Convenience function for generating functional data	simulation_model9
Spanish Weather Data	spanish_weather
Total Variation Depth and Modified Shape Similarity Index	total_variation_depth
Outlier detection using the total variation depth and modified shape similarity index.	tvdmss tvd_mss
World Population Data by Countries	world_population

Package: fdaoutlier 0.2.1

fdaoutlier: Outlier Detection Tools for Functional Data Analysis

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