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 ...

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 ...

VAR models analyse and predict multivariate time series data, unlike univariate autoregressive models. These models are particularly useful in fields such as economics and weather forecasting. VAR ...

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 ...

In a landmark contribution to the structural vector autoregression (SVARs) literature, Rubio-Ramirez, Waggoner, and Zha (2010, `Structural Vector Autoregressions: Theory of Identification and ...

Since two people came down a county of north Seattle with positive COVID-19 (coronavirus-19) in 2019, the current total cases in the United States (U.S.) are over 12 million. Predicting the pandemic ...

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 ...