CRAN/E | FSMUMI

FSMUMI

Imputation of Time Series Based on Fuzzy Logic

Installation

About

Filling large gaps in low or uncorrelated multivariate time series uses a new fuzzy weighted similarity measure. It contains all required functions to create large missing consecutive values within time series and then fill these gaps, according to the paper Phan et al. (2018), doi:10.1155/2018/9095683. Performance indicators are also provided to compare similarity between two univariate signals (incomplete signal and imputed signal).

Citation FSMUMI citation info
mawenzi.univ-littoral.fr/FSMUMI/

Key Metrics

Version 1.0
R ≥ 3.0.0
Published 2018-11-26 1980 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks FSMUMI results

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Maintainer

Maintainer

Thi Thu Hong Phan

ptthong@vnua.edu.vn

Authors

Thi-Thu-Hong Phan
Andre Bigand
Emilie Poisson-Caillault

Material

Reference manual
Package source

In Views

MissingData

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

Depends

R ≥ 3.0.0

Imports

FuzzyR
stats
lsa