Probabilistic Forecast Combination Using CRPS Learning
Autoplot method for batch models
Autoplot method for online models
Probabilistic Forecast Combination - Batch
Create an conline Object from the conline C++ Class
Create experts list to be used in conline class
Create a List of Basis Matrices
Create a List of Hat Matrices
Create a vector of knots for splines
Probabilistic Forecast Combination - Online
Probabilistic Forecast Combination - Oracle
B-Spline penalty
Plot method for batch models
Plot method for online models
Post Process Data from conline Class
Predict method for online models
Print method for batch models
Print method for online models
Package Info
Objects exported from other packages
Create B-Spline basis
Summary method for online models
Tidy the Experts' losses of an Online object
Tidy the Experts' losses of an Online object
Tidy the Predictions of an Online object
Tidy the Weights of an Online object
Update method for online models
Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) <doi:10.48550/arXiv.2102.00968> <doi:10.1016/j.jeconom.2021.11.008>. The package implements multiple online learning algorithms like Bernstein online aggregation; see Wintenberger (2014) <doi:10.48550/arXiv.1404.1356>. Quantile regression is also implemented for comparison purposes. Model parameters can be tuned automatically with respect to the loss of the forecast combination. Methods like predict(), update(), plot() and print() are available for convenience. This package utilizes the optim C++ library for numeric optimization <https://github.com/kthohr/optim>.
Useful links