The advanced statistical methods in aerobiological studies

Abstract

Pollen and spore forecasting has become an important aim in aerobiology. The main goal is to provide accurate information on biological particles in the air to sensitive users in order to help them optimize their treatment process. Many statistical methods of data analysis are based on the assumptions of linearity and normality that often cannot be fulfilled. The advanced statistical methods can be applied to the problems that cannot be solved in any other effective way, and are suited to predicting the concentration of airborne pollen or spores in relation to weather conditions. The purpose of the study was to review some advanced statistical methods that can be used in aerobiological studies.

Keywords

• aeroplankton
• pollen and fungal spores
• forecasting
• artificial neural network (ANN)
• multivariate regression tree (MRT)
• canonical correspondence analysis (CCA)