CRAN/E | EFDR

EFDR

Wavelet-Based Enhanced FDR for Detecting Signals from Complete or Incomplete Spatially Aggregated Data

Installation

About

Enhanced False Discovery Rate (EFDR) is a tool to detect anomalies in an image. The image is first transformed into the wavelet domain in order to decorrelate any noise components, following which the coefficients at each resolution are standardised. Statistical tests (in a multiple hypothesis testing setting) are then carried out to find the anomalies. The power of EFDR exceeds that of standard FDR, which would carry out tests on every wavelet coefficient: EFDR choose which wavelets to test based on a criterion described in Shen et al. (2002). The package also provides elementary tools to interpolate spatially irregular data onto a grid of the required size. The work is based on Shen, X., Huang, H.-C., and Cressie, N. 'Nonparametric hypothesis testing for a spatial signal.' Journal of the American Statistical Association 97.460 (2002): 1122-1140.

Citation EFDR citation info
github.com/andrewzm/EFDR/

Key Metrics

Version 1.3
R ≥ 3.5.0
Published 2023-08-22 237 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks EFDR results

Downloads

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Maintainer

Maintainer

Andrew Zammit-Mangion

andrewzm@gmail.com

Authors

Andrew Zammit-Mangion

aut / cre

Hsin-Cheng Huang

aut

Material

Reference manual
Package source

Vignettes

Enhanced False Discovery Rate (EFDR) tutorials

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

EFDR archive

Depends

R ≥ 3.5.0

Imports

copula
Matrix
methods
foreach ≥ 1.4.2
doParallel ≥1.0.8
waveslim ≥ 1.7.5
parallel
gstat ≥ 1.0-19
tidyr ≥ 0.1.0.9000
dplyr ≥ 0.3.0.2
sp ≥ 1.0-15

Suggests

knitr
rmarkdown
markdown
ggplot2
RCurl
fields
gridExtra
animation