FSMUMImputation: Imputing large gaps based on the new fuzzy-weighted...
In FSMUMI: Imputation of Time Series Based on Fuzzy Logic
Description
Usage
Arguments
Value
Author(s)
View source: R/FSMUMImputation.R
Description
Fill large gaps in low or uncorrelated multivariate time series using the fuzzy-weighted similarity measure
Usage
1
FSMUMImputation(data, large_gap_threshold, step_threshold, step_finding)
Arguments
data
a multivariate signals containing gaps
large_gap_threshold
threshold used to determine a gap is large
step_threshold
increment used for finding the threshold
step_finding
increment used for retrieving a similar sequences to the queries
Value
returns a completed multivariate time series
Author(s)
Thi-Thu-Hong Phan, Andre Bigand, Emilie Poisson-Caillault
FSMUMI documentation built on May 2, 2019, 12:40 p.m.
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Description Usage Arguments Value Author(s)
View source: R/FSMUMImputation.R
Description
Fill large gaps in low or uncorrelated multivariate time series using the fuzzy-weighted similarity measure
Usage
1 | FSMUMImputation(data, large_gap_threshold, step_threshold, step_finding)
|
Arguments
data |
a multivariate signals containing gaps |
large_gap_threshold |
threshold used to determine a gap is large |
step_threshold |
increment used for finding the threshold |
step_finding |
increment used for retrieving a similar sequences to the queries |
Value
returns a completed multivariate time series
Author(s)
Thi-Thu-Hong Phan, Andre Bigand, Emilie Poisson-Caillault
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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