[
Barańska, A., & Łuczak, A. (2007). Comparing the results of function model estimation for the prediction of real estate market values in additive and multiplicative form. Geomatics and Environmental Engineering, 1(3), 19–35.
]Search in Google Scholar
[
Cellmer, R., Cichulska, A., & Bełej, M. (2020). Spatial Analysis of Housing Prices and Market Activity with the Geographically Weighted Regression. ISPRS International Journal of Geo-Information, 9(6), 380. https://doi.org/10.3390/ijgi9060380
]Search in Google Scholar
[
Dell, G. (2017). Regression, Critical Thinking, and the Valuation Problem Today. The Appraisal Journal, 85(3), 217–230.
]Search in Google Scholar
[
Doszyń, M. (red. n.). (2020a). System kalibracji macierzy wpływu atrybutów w szczecińskim algorytmie masowej wyceny nieruchomości. WNUS. Szczecin [Doszyń, M. (red. n.) (2020a). Calibration system of attributes influence matrix in Szczecin mass real estate valuation algorithm. WNUS. Szczecin]
]Search in Google Scholar
[
Doszyń, M. (2020b). Algorithm of real estate mass appraisal with inequality restricted least squares (IRLS) estimation. Journal of European Real Estate Research, 13(2), 161–179. https://doi.org/10.1108/JERER-11-2019-0040
]Search in Google Scholar
[
Doszyń, M. (2021). Prior information in econometric real estate appraisal: A mixed estimation procedure. Journal of European Real Estate Research, 14(3), 349–361. https://doi.org/10.1108/JERER-11-2020-0057
]Search in Google Scholar
[
Doszyń, M. (2022). Might expert knowledge improve econometric real estate mass appraisal? The10.1007/s11146-022-09891-3
]Search in Google Scholar
[
Journal of Real Estate Finance and Economics. Advance online publication. https://doi.org/10.1007/s11146-022-09891-3
]Search in Google Scholar
[
Durbin, J. (1953). A Note on Regression When There is Extraneous Information About One of the Coefficients. Journal of the American Statistical Association, 48(264), 799–808. https://doi.org/10.1080/01621459.1953.10501201
]Search in Google Scholar
[
Fik, T. J., Ling, D. C., & Mulligan, G. F. (2003). Modelling Spatial Variation in Housing Prices: A Variable Interaction Approach. Real Estate Economics, 31(4), 623–646. https://doi.org/10.1046/j.1080-8620.2003.00079.x
]Search in Google Scholar
[
Grömping, U. (2010). Inference with Linear Equality and Inequality Constraints Using R: The Package ic.infer. Journal of Statistical Software, 33(10), 1–31. https://doi.org/10.18637/jss.v033.i10
]Search in Google Scholar
[
Hozer, J., Foryś, I., Zwolankowska, M., Kokot, S., & Kuźmiński, W. (1999). Ekonometryczny algorytm masowej wyceny nieruchomości gruntowych. [Econometric algorithm of land property mass appraisal]. Uniwersytet Szczeciński, Stowarzyszenie „Pomoc i Rozwój”, Szczecin
]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. https://doi.org/10.1080/10835547.1998.12090922
]Search 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
[
Kokot, S., & Gnat, S. (2019). Simulative Verification of the Possibility of Using Multiple Regression Models for Real Estate Appraisal. Real Estate Management and Valuation, 27(3), 109–123. https://doi.org/10.2478/remav-2019-0029
]Search in Google Scholar
[
McCluskey, W. J., McCord, M., Davis, P. T., Haran, M., & McIlhatton, D. (2013). Prediction Accuracy in Mass Appraisal: A Comparison of Modern Approaches. Journal of Property Research, 30(4), 239–265. https://doi.org/10.1080/09599916.2013.781204
]Search in Google Scholar
[
Mehta, J. S., & Swamy, P. A. V. B. (1970). The Finite Sample Distribution of Theil’s Mixed Regression Estimator and a Related Problem. Review of the International Statistical Institute, 38(2), 202–209. https://doi.org/10.2307/1402143
]Search in Google Scholar
[
Mittelhammer, R. C., & Conway, R. K. (1988). Applying Mixed Estimation in Econometric Research. American Journal of Agricultural Economics, 70(4), 859–866. https://doi.org/10.2307/1241927
]Search in Google Scholar
[
Nagar, A. L., & Kakwani, N. C. (1964). The Bias and Moment Matrix of a Mixed Regression Estimator. Econometrica, 32(1/2), 174–182. https://doi.org/10.2307/1913742
]Search in Google Scholar
[
Pace, R. K., & Gilley, O. W. (1990). Estimation employing a priori information within mass appraisal and hedonic pricing models. The Journal of Real Estate Finance and Economics, 3(1), 55–72. https://doi.org/10.1007/BF00153706
]Search in Google Scholar
[
Pace, R. K. (1995). Parametric, semiparametric, and nonparametric estimation of characteristic values within mass assessment and hedonic pricing models. The Journal of Real Estate Finance and Economics, 11, 195–217. https://doi.org/10.1007/BF01099108
]Search in Google Scholar
[
Pagourtzi, E., Assimakopoulos, V., Hatzichristos, T., & French, N. (2003). Real Estate Appraisal: A Review of Valuation Methods. Journal of Property Investment & Finance, 21(4), 383–401. https://doi.org/10.1108/14635780310483656
]Search in Google Scholar
[
Sing, T. F., Yang, J. J., & Yu, S. M. (2021). Boosted Tree Ensembles for Artificial Intelligence Based Automated Valuation Models (AI-AVM). The Journal of Real Estate Finance and Economics. Advance online publication. https://doi.org/10.1007/s11146-021-09861-1
]Search in Google Scholar
[
Swamy, P. A. V. B., & Mehta, J. S. (1969). On Theil’s Mixed Regression Estimator. Journal of the American Statistical Association, 64(325), 273–276. https://doi.org/10.1080/01621459.1969.10500969
]Search in Google Scholar
[
Theil, H., & Goldberger, A. S. (1961). On Pure and Mixed Statistical Estimation in Economics. International Economic Review, 2(1), 65–78. https://doi.org/10.2307/2525589
]Search in Google Scholar
[
Theil, H. (1963). On the Use of Incomplete Prior Information in Regression Analysis. Journal of the American Statistical Association, 58(302), 401–414. https://doi.org/10.1080/01621459.1963.10500854
]Search 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, 349–388. https://doi.org/10.1080/10835547.2011.12091311
]Search in Google Scholar
