Abstract: This paper presents macroeconomic forecasting by using a time-varying Bayesian compressed vector autoregression approach. We apply a random compression by using projection matrix to randomly ...

An econometrics vector autoregression model (VAR) for analysis of multivariate time series of macroeconomics phenomena. Python Jupyter notebook based model is presented here although other packages ...

Autoregressive image generation models have traditionally relied on vector-quantized representations, which introduce several significant challenges. The process of vector quantization is ...

Forecasting solar irradiance is a critical task in the renewable energy sector, as it provides essential information regarding the potential energy production from solar panels. This study aims to ...

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Abstract: Advanced time series models have been intensively developed and used to predict in financial data such as foreign exchange data (forex). In this paper, we implement the random compression ...

This study aims to build an efficient small-scale macroeconomic forecasting tool for Maldives using Bayesian vector autoregression estimations to circumvent the "curse of dimensionality" and ...

This code is a demonstration of how to implement a VAR model. I estimate the VAR coefficients and then compare those with the results from a statsmodels package. The results are identical. This is a ...