FSMUMI: Imputation of Time Series Based on Fuzzy Logic

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).

Package details

AuthorThi-Thu-Hong Phan, Andre Bigand, Emilie Poisson-Caillault
MaintainerThi Thu Hong Phan <ptthong@vnua.edu.vn>
LicenseGPL (>= 2)
URL http://mawenzi.univ-littoral.fr/FSMUMI/
Package repositoryView on CRAN
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FSMUMI documentation built on May 2, 2019, 12:40 p.m.