Using Kernel density estimation for modelling and simulating transaction location

Abstract

Simulation modelling performs a prognostic function through model research and the shaping of the future. Thorough insight into the analysed system and exploring its characteristics for the selection of optimal tools of analysis is an extremely significant process that precedes the stage of the simulation itself. For modelling and transaction simulation, the problem concerning the optimal range of the kernel function used for exploring the spatial activity of a property market should be addressed first. A probability function is the basis for the subsequent phase of research, which allows one to answer the question of whether the transaction density in a given year can be reflected in the transactions of the following year and subsequent years, and whether transaction distribution is correlated, in any way, with the transaction density in the previous year. The final results of the work are maps of the dynamics of transactions on the market and of the simulated transaction density.

Keywords

• Real estate market
• Simulation modelling
• Kernel density estimation
• Transaction density
• Map of transaction