lpd_features_multi: Compute log predictive densities and features
In lily940703/febama: Feature-based Bayesian Forecasting Model Averaging
View source: R/densities_features.R
lpd_features_multi R Documentation
Compute log predictive densities and features
Description
Compute log predictive densities and features for training in FEBAMA framework.
Usage
lpd_features_multi(data, model_conf)
Arguments
data
A list with related information of a time series. Historical data x is neccessary.
model_conf
Parameter settings of FEBAMA framework. Defualt model_conf_default().
Value
A list with log predictive densities and features.
lily940703/febama documentation built on March 20, 2022, 1:57 a.m.
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View source: R/densities_features.R
| lpd_features_multi | R Documentation |
Compute log predictive densities and features
Description
Compute log predictive densities and features for training in FEBAMA framework.
Usage
lpd_features_multi(data, model_conf)
Arguments
data |
A list with related information of a time series. Historical data |
model_conf |
Parameter settings of FEBAMA framework. Defualt |
Value
A list with log predictive densities and features.
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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