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GAMP-regression

The GitHub repository contains an implementation of the Generalized Approximate Message Passing (GAMP) algorithm for macroeconomic forecasting using known variance and prior hyperparameters. The source code in this repository is sourced from Dr. Dimitris Korobilis' website, which accompanies his research article "High-dimensional macroeconomic forecasting using message passing algorithms" published in the Journal of Business & Economic Statistics in 2019.

The GAMP algorithm is a widely used method for solving large-scale inference problems with complex probability distributions. It can be used to estimate the parameters of macroeconomic models and forecast macroeconomic variables such as GDP, inflation, and unemployment rates.

Overall, this repository provides a valuable resource for researchers and practitioners interested in macroeconomic forecasting using the GAMP algorithm. The implementation is based on a well-regarded research article, making it a valuable tool for those exploring the use of message passing algorithms in high-dimensional forecasting problems.

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Generalized Approximate Message Passsing (GAMP) with known variance and prior hyperparameters for regression

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