You may be able to download this chapter for free via the Document Object Identifier. What should applied macroeconomists know about local projection (LP) and vector ...

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 ...

Objective: This study aimed to develop depression incidence forecasting models and compare the performance of autoregressive integrated moving average (ARIMA) and vector-ARIMA (VARIMA) and temporal ...

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 ...

Abstract: Finding the best vector autoregression model for any dataset, medical or otherwise, is a process that, to this day, is frequently performed manually in an iterative manner requiring a ...

In analogy to biological synapses, two terminal solid state nanodevices such as ReRAM can store synaptic weights as electrical resistance states. The devices, consisting simply of patterned ...