Nothing
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).
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Thi-Thu-Hong Phan, Andre Bigand, Emilie Poisson-Caillault |
| Maintainer | Thi Thu Hong Phan <ptthong@vnua.edu.vn> |
| License | GPL (>= 2) |
| Version | 1.0 |
| URL | http://mawenzi.univ-littoral.fr/FSMUMI/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the FSMUMI package in your browser
Any scripts or data that you put into this service are public.
