Forecast uncertainty based on model averaging
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Updated
May 27, 2021 - R
Forecast uncertainty based on model averaging
Out-Of-Sample Time Series Forecasting: OOS introduces a comprehensive framework for time series forecasting with traditional econometric and modern machine learning techniques.
This code mainly computes the forecast of headline inflation using different aproaches. Likewise presents the forecast evaluation for each model along different points in a span period.
This repository contains the R-Package for a novel time series forecasting method designed to handle very large sets of predictive signals, many of which are irrelevant or have only short-lived predictive power.
Honours research project for Sapphire Li (2023)
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