calculate_MSIS: Benchmarking the perforamance of Similarity against ETS and...
In kdwang1808/Dejavu: Deja vu: forecasting with similarity
Description
Usage
Arguments
Value
References
View source: R/calculate_MSIS.R
Description
Benchmarking the perforamance of Similarity against ETS and SHD
Usage
1
calculate_MSIS(tsi, gamma = 0.05, fh, nts = 100, Dist_type = 3)
Arguments
tsi
ith particular reference series
gamma
calibrated significance level quantiles
fh
number of forecasting horizon
nts
number of the most similar series
Dist_type
number of forecasting benchmarks
Value
Dataframe containing theaccuracy of MSIS, Coverage, Upper coverage, Spread and MASE
using ETS, SHD, Similarity and ETS-Similarity separately
References
Svetunkov & Petropoulos (2018)
kdwang1808/Dejavu documentation built on March 23, 2020, 5:14 a.m.
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Description Usage Arguments Value References
View source: R/calculate_MSIS.R
Description
Benchmarking the perforamance of Similarity against ETS and SHD
Usage
1 | calculate_MSIS(tsi, gamma = 0.05, fh, nts = 100, Dist_type = 3)
|
Arguments
tsi |
ith particular reference series |
gamma |
calibrated significance level quantiles |
fh |
number of forecasting horizon |
nts |
number of the most similar series |
Dist_type |
number of forecasting benchmarks |
Value
Dataframe containing theaccuracy of MSIS, Coverage, Upper coverage, Spread and MASE using ETS, SHD, Similarity and ETS-Similarity separately
References
Svetunkov & Petropoulos (2018)
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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