Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/26454| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Natasha Malijanska, Sanja Atanasova, Gjorgji Gjorgjiev, Igor Peshevski, Daniel Velinov | en_US |
| dc.date.accessioned | 2023-05-11T09:34:56Z | - |
| dc.date.available | 2023-05-11T09:34:56Z | - |
| dc.date.issued | 2022 | - |
| dc.identifier.uri | http://hdl.handle.net/20.500.12188/26454 | - |
| dc.description.abstract | Real estate mass valuation models of a market value have a tendency to generate real estate property values as close as to the real market values. Property valuation theory, as one of the primary factors influencing property value, considers location. The main statistical tool used for modelling in this investigation is geographically weighted regression. More precisely, the paper is striving to establish a mass valuation real estate property model considering the implementation of spatial data as a significant factor in determining the market value of condominiums in Skopje. | en_US |
| dc.subject | Geographically weighted regression approach, multivariate regression, sensitive analysis, real estate mass valuation | en_US |
| dc.title | A GEOGRAPHICALLY WEIGHTED REGRESSION APPROACH IN REGIONAL MODEL FOR REAL ESTATE MASS VALUATION | en_US |
| dc.type | Article | en_US |
| dc.relation.conference | II Congress of Differential Equations, Mathematical Analysis and Applications CODEMA 2022 X Seminar of Differential Equations and Analysis, September 25 - September 28, 2022. | en_US |
| item.grantfulltext | open | - |
| item.fulltext | With Fulltext | - |
| Appears in Collections: | Faculty of Electrical Engineering and Information Technologies: Conference Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 22_A-georgaphically-weighted-regression-approach-in-regional-model-CODEMA-2022-Copy.pdf | 1.26 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.