dimension_ensemble: model ensemble
In babdebuba/ftsmp: Forecasting time series with many predictors
Description
Usage
Arguments
Value
Description
forecast using dms
Usage
1
2
dimension_ensemble(yraw, alpha, gg, kk, ll, pp, cores_number, hh,
prior_constant_variance, density_size, sub, dimensions)
Arguments
yraw
data
alpha
forgetting factor
gg
state variance
kk
observation variance
ll
prior parameter
pp
lags
cores_number
number of parallel cores
hh
forecast horizon
prior_constant_variance
expecttaion prior choice
density_size
density_size
sub
sub models for dms
dimensions
variable to forecast
Value
forecasts and probability of the models
babdebuba/ftsmp documentation built on May 11, 2019, 5:22 p.m.
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Description Usage Arguments Value
Description
forecast using dms
Usage
1 2 | dimension_ensemble(yraw, alpha, gg, kk, ll, pp, cores_number, hh,
prior_constant_variance, density_size, sub, dimensions)
|
Arguments
yraw |
data |
alpha |
forgetting factor |
gg |
state variance |
kk |
observation variance |
ll |
prior parameter |
pp |
lags |
cores_number |
number of parallel cores |
hh |
forecast horizon |
prior_constant_variance |
expecttaion prior choice |
density_size |
density_size |
sub |
sub models for dms |
dimensions |
variable to forecast |
Value
forecasts and probability of the models
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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