Nowadays, air pollution forecasting modeling is vital to achieve an increase in air quality,
allowing an improvement of ecosystems and human health. It is important to consider the …

Coronavirus pandemic has affected the whole world extensively and it is of immense
importance to understand how the disease is spreading. In this work, we provide evidence of …

Latent factor models can perform spatio-temporal forecasting (ie, predicting future responses
at unmeasured as well as measured locations) by modeling temporal dependence using …

Statistical research in real estate markets, particularly in understanding the spatio-temporal
dynamics of house prices, has garnered significant attention in recent times. Although …

This study analyses seasonal and regular variations in ambient atmospheric concentrations
of total gaseous mercury (TGM), ancillary air pollutant concentrations, and their relationship …

The paper goal is to develop a spatial analyses of the most critical environmental issues in
the country and how the population concerns could be addressed with the use of spatial …

Smog in China has been a major issue in recent years. As the main component of smog, PM
2.5 has received a lot of attention from the public, as the pollution caused by PM 2.5 is …

This thesis explores how state space models, which are a type of econometric models
designed to analyse time series data, can be employed to achieve more accurate and …

In this article the main topic of interest is to explore the analyzing possibilities offered by the
latest version of ArcGIS Pro. At the same time, we want to highlight the use the 2D and 3D …

Count data appears in various disciplines. In this work, a new method to analyze time series
count data has been proposed. The method assumes exponentially decaying covariance …