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Application of Multivariate Time Series Cluster Analysis to Regional Socioeconomic Indicators of Municipalities. (2021). Andrius, Kriinas ; Valentas, Gruauskas ; Tautvydas, Fyleris ; Dalia, Alneryt.
In: Real Estate Management and Valuation.
RePEc:vrs:remava:v:29:y:2021:i:3:p:39-51:n:4.

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  1. Asamoah, R. O., Baiden, B. K., Nani, G., & Kissi, E. (2019). Review of exogenous economic indicators influencing construction industry. Advances in Civil Engineering, 2019, 1–8. Advance online publication. https://doi.org/10.1155/2019/6073289 Athey, S. (2019). The Impact of Machine Learning on Economics. The Economics of Artificial Intelligence: An Agenda,. 548–551.
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  2. Athey, S., & Luca, M. (2019). Economists (and economics) in tech companies. The Journal of Economic Perspectives, 33(1), 209–230. https://doi.org/10.1257/jep.33.1.209 Augustyński, I., & Laskoś-Grabowski, P. (2018). Clustering macroeconomic time series. econometrics, 22(2), 74–88. https://doi.org/10.15611/eada.2018.2.06 Blien, U., Hirschenauer, F., & Thi Hong Van, P. (2010). Classification of regional labour markets for purposes of labour market policy. Papers in Regional Science, 89(4), 859–880. https://doi.org/10.1111/j.1435-5957.2010.00331.x Brauksa, I. (2013). Use of Cluster Analysis in Exploring Economic Indicator Differences among Regions: The Case of Latvia. Journal of Economics, Business and Management, 1(1), 42–45.

  3. Journal of the American Geriatrics Society, 63(5), 993–996. https://doi.org/10.1111/jgs.13392 PMID:25940710 Nugroho, A. A., Purnama, M. Y. I., & Fauzia, L. R. (2020). Clustering and regional growth in the housing market: Evidence from Indonesia. Jurnal Keuangan Dan Perbankan, 24(1), 83–94. https://doi.org/10.26905/jkdp.v24i1.3565 Řezanková, H. (2014). Cluster analysis of economic data. Statistika, 94(1), 73–86.
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  4. Neurocomputing, 349, 239–247. https://doi.org/10.1016/j.neucom.2019.03.060 Majerova, I., & Nevima, J. (2017). The measurement of human development using the ward method of cluster analysis. Journal of International Students, 10(2), 239–257. https://doi.org/10.14254/20718330. 2017/10-2/17 Manzhynski, S., Siniak, N., Źróbek-Różańska, A., & Źróbek, S. (2016). Sustainability performance in the Baltic Sea Region. Land Use Policy, 57, 489–498. https://doi.org/10.1016/j.landusepol.2016.06.003 REAL ESTATE MANAGEMENT AND VALUATION, eISSN: 2300-5289 51 www.degruyter.com/view/j/remav vol. 29, no. 3, 2021 Mattes, M. D., & Sloane, M. A. (2015). Reflections on Hope and Its Implications for End-of-Life Care.
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  5. Rovan, J., & Sambt, J. (2003). Socio-economic Differences Among Slovenian Municipalities : A Cluster Analysis Approach. Developments in Applied Statistics.
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  1. Application of Multivariate Time Series Cluster Analysis to Regional Socioeconomic Indicators of Municipalities. (2021). Andrius, Kriinas ; Valentas, Gruauskas ; Tautvydas, Fyleris ; Dalia, Alneryt.
    In: Real Estate Management and Valuation.
    RePEc:vrs:remava:v:29:y:2021:i:3:p:39-51:n:4.

    Full description at Econpapers || Download paper

  2. Inefficiencies in Digital Advertising Markets. (2020). Gordon, Brett ; Katona, Zsolt ; Narayanan, Sridhar ; Jerath, Kinshuk ; Wilbur, Kenneth C ; Shin, Jiwoong.
    In: Papers.
    RePEc:arx:papers:1912.09012.

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