Analysis of the Impact of the Type of Sampling of Representative Properties on the Results of Mass Appraisal

Antipov, E.A., Pokryshevskaya, E.B. (2012). Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics. Expert Systems with Applications, 39 (2), 1772–1778. DOI: 10.1016/j. eswa.2011.08.077.Search in Google Scholar

Benjamin, J.D., Randall, S., Guttery, R.S., Sirmans, C.F. (2004). Mass Appraisal: An Introduction to Multiple Regression Analysis for Real Estate Valuation. Journal of Real Estate Practice and Education, 7 (1), 65–77. DOI: 10.1080/10835547.2004.12091602.10.1080/10835547.2004.12091602Search in Google Scholar

Burgard, J.P., Münnich, R., Zimmermann, T. (2014). The Impact of Sampling Designs on Small Area Estimates for Business Data. Journal of Official Statistics, 30 (4). 749-771. DOI: 10.2478/jos-2014-0046.10.2478/jos-2014-0046Search in Google Scholar

Chun & Griffith (2013). Spatial statistics and geostatistics, SAGE: Los Angeles.Search in Google Scholar

Ćetković, J., Slobodan, L., Lazarevska, L., Žarković, M., Vujošević, S., Cvijović, J., Gogić, M. (2018). Assessment of the Real Estate Market Value in the European Market by Artificial Neural Networks Application. Complexity 2018. DOI: 10.1155/2018/1472957.10.1155/2018/1472957Search in Google Scholar

Dell, G. (2017). Regression, Critical Thinking, and the Valuation Problem Today. Appraisal Journal, 85 (3), 217–230.Search in Google Scholar

Dmytrów, K., Gnat, S. (2019). Application of AHP Method in Assessment of the Influence of Attributes on Value in the Process of Real Estate Valuation, Real Estate Management and Valuation, 27 (4), 15–26. DOI: 10.2478/remav-2019-0032.10.2478/remav-2019-0032Search in Google Scholar

Doszyń, M., Gnat, S., Bas, M. (2017). The Econometric Procedures of Specific Transactions Identification. Folia Oeconomica Stetinensia, 17 (1), 20–30. DOI: 10.1515/foli-2017-0002.10.1515/foli-2017-0002Search in Google Scholar

Doszyń, M. (2012). Ekonometryczna wycena nieruchomości. Studia i Prace Wydziału Nauk Ekonomicznych i Zarządzania Uniwersytetu Szczecińskiego, 26, 41–52.Search in Google Scholar

Doszyń, M. (ed.) (2020). System kalibracji macierzy wpływu atrybutów w szczecińskim algorytmie masowej wyceny nieruchomości. Szczecin: Wydawnictwo Naukowe Uniwersytetu Szczecińskiego.Search in Google Scholar

Hozer, J., Gnat, S., Kokot, S., Kuźmiński, W. (2019). The Problem of Designating Elementary Terrains for the Purpose of Szczecin Algorithm of Real Estate Mass Appraisal. Real Estate Management and Valuation, 27 (3), 42–58. DOI: 10.2478/remav-2019-0024.10.2478/remav-2019-0024Search in Google Scholar

Etikan, I., Musa, S.A., Alkassim, R.S. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5 (1), 1–4. DOI: 10.11648/j.ajtas.20160501.11.10.11648/j.ajtas.20160501.11Search in Google Scholar

Hozer, J., Kokot, S., Kuźmiński, W. (2002), Methods of statistical market analysis in real estate valuation. Warsaw: Polish Federation of Valuers’ Associations.Search in Google Scholar

Isakson, H.R. (1998). The Review of Real Estate Appraisals Using Multiple Regression Analysis. Journal of Real Estate Research, 15 (2), 177–190.10.1080/10835547.1998.12090922Search in Google Scholar

Jahanshiri, E., Buyong, T., Shariff, A.R.M. (2011). A review of Property Mass Valuation Models. Pertanika Journal of Science & Technology, 19, 23–30.Search in Google Scholar

Kauko, T., d’Amato, M. (2008). Mass Appraisal Methods: An International Perspective for Property Valuers. Blackwell Publishing Ltd.10.1002/9781444301021Search in Google Scholar

Kilpatrick, J. (2011). Expert Systems and Mass Appraisal. Journal of Property Investment & Finance, 29 (4/5), 529–550. DOI: 10.1108/14635781111150385.10.1108/14635781111150385Search in Google Scholar

Lahiri, P. (2003). On the Impact of Bootstrap in Survey Sampling and Small-Area Estimation. Statistical Science, 18 (2), 199–210. DOI: 10.1214/ss/1063994975.10.1214/ss/1063994975Search in Google Scholar

McCluskey, W.J., Daud, D.Z., Kamarudin, N. (2014). Boosted regression trees: An application for the mass appraisal of residential property in Malaysia. Journal of Financial Management of Property and Construction, 19 (2), 152–167. DOI: 10.1108/JFMPC-06-2013-0022.10.1108/JFMPC-06-2013-0022Search in Google Scholar

Rao, J.N.K. (2011). Impact of Frequentist and Bayesian Methods on Survey Sampling Practice: A Selective Appraisal. Statistical Science, 26 (2), 240–256. DOI: 10.1214/10-STS346.10.1214/10-STS346Search in Google Scholar

Schreuder, H.T., Gregoire, T.G., Weyer, J.P. (2001). For what applications can probability and non-probability sampling be used? Environmental Monitoring and Assessment, 66, 281–291. DOI: 10.1023/A:1006316418865.10.1023/A:1006316418865Search in Google Scholar

Wang, X., Wen, J., Zhang, Y., Wang, Y. (2014). Real estate price forecasting based on SVM optimized by PSO. Optik, 125 (3), 1439–1443. DOI: 10.1016/j.ijleo.2013.09.017.10.1016/j.ijleo.2013.09.017Search in Google Scholar

Zurada, J., Levitan, A.S., Guan, J. (2011). A Comparison of Regression and Artificial Intelligence Methods in a Mass Appraisal Context. Journal of Real Estate Research, 33 (3), 349–387. DOI: 10.1080/10835547.2011.12091311.10.1080/10835547.2011.12091311Search in Google Scholar