Research Article
Year 2020,
Volume: 46 Issue: 2, 85 - 102, 31.10.2020
Abstract
This study aimed at determining the number of problems affecting e-commerce factor for Turkey. For this purpose, count data models were used. Poisson (P), negative binomial (NB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), Poisson Hurdle (PH) and negative binomial Hurdle (NBH) regression models have been applied. It has been decided by using Akaike Information Criteria, log likelihood, Vuong, Rootogram goodness of fit tests which model represents the data set better. According to the results of analysis, it was seen that ZINB model should be preferred. In addition, the parameters of the ZINB model were examined and interpreted.
References
- Açıkyürek, Gizem. (2016). Poisson Regresyon ve Bir Uygulama. Yayınlanmış Yüksek Lisans Tezi. Hacettepe Üniversitesi, Fen Bilimleri Enstitüsü, Ankara. Agresti, A. (2002). Categorical Data Analysis (Second Edition), New Jersey: Wiley & Sons Incorporation. Altun, E. (2018). A New Zero-Inflated Regression Model With Application. İstatistikçiler Dergisi: İstatistik ve Aktüerya, 11(2), 73-80. Asrul A.A.M. and Naingb, N.N. (2012). Analysis Death Rate of Age Model with Excess Zeros using Zero Inflated Negative Binomial and Negative Binomial Death Rate: Mortality AIDS Co-Infection Patients, Kelantan Malaysia. Procedia Economics and Finance, 2(2012), 275-283. Beaujean A.A. and Morgan G.B. (2016, February). Tutorial on Using Regression Models with Count Outcomes Using R. Practical Assessment Research & Evaluation, 21(2), 1531-7714. Cameron, A.C. and Trivedi, P.K. (2013). Regression Analysis of Count Data (Second Edition), New York: Cambridge University Press Carrivick, P.J.W., Lee, A.H. and Yau, K.K.W. (2003). Zero-inflated Poisson Modeling to Evaluate Occupational Safety Interventions. Safety Science, 41(1), 53-63. Canpolat, Ö. (2001). E-ticaret ve Türkiye'deki gelişmeler. Sanayi ve Ticaret Bakanlığı. ÇİLAN, Ç. A., & Sultan, K. U. Z. U. (2013). Kişisel E-Ticaret Uygulamalarının Kategorik Veri Analizi Yöntemleri İle Değerlendirilmesi. Alphanumeric Journal, 1(1), 27-32. Fang, R., (2013). Zero-Inflated Negative Binomial (ZINB) Regressıon Model for Over Dispersed Count Data with Excess Zeros and Repeated Measures an Application to Human Microbiota Sequence Data. Yüksek Lisans Tezi. Greene, W. H., 1994. Accounting For Excess Zeros And Sample Selection In Poisson And Negative Binomial Regression Models. New York University Department of Economics Working Paper , 94-10. Hilbe, J. M. (2014). Modelling Count Data (First Edition), New York: Cambridge University Press. Ismail, N., ve Zamani, H. (2013). Estimation Of Claimcount Data Using Negative Binomial, Generalized Poisson, Zero-İnflated Negative Binomial And Zero-İnflated Generalized Poisson Regression Models. In Casualty Actuarial Society E-Forum (Vol. 41, No. 20, pp. 1-28). İnternet: http://www.tuik.gov.tr/PreHaberBultenleri.do?id=30574 Kaya, Y., ve Yeşilova, A. (2012). E-Posta Trafiğinin Sıfır Değer Ağırlıklı Regresyon Yöntemleri Kullanılarak İncelenmesi. Anadolu University of Sciences & Technology-A: Applied Sciences & Engineering, 13(1). Karaca, A. G., ve Olmuş, H. (2018). Sıfır Değer Ağırlıklı Verilerin Analizinde Sıfır Değer Ağırlıklı Regresyon Modellerin İncelenmesi. Trakya Üniversitesi Sosyal Bilimler Dergisi, 20(2), 105-118. Karaca, A,. G. (2018). Sayma Verileri İçin Regresyon Modellerinin Karşılaştırılması Üzerine Bir Uygulama. Yayımlanmış Yüksek Lisans Tezi. Gazi Üniversitesi Fen Bilimleri Enstitüsü, Ankara. Kong, M., Xu, S., Levy, S.M. and Datta, S. (2014). “GEE Type Inference for Clustered Zero-Inflated Negative Binomial Regression with Application to Dental Caries”. Computational Statistics and Data Analysis, 85, 54-66. Kleiber, C., Zeileis, A., Visualizing Count Data Regressions using Rootograms. The American Statistician, 70(3), 296-303, 2016. Kim, D. W., Deo, R. C., Park, S. J., Lee, J. S., & Lee, W. S. (2019). Weekly Heat Wave Death Prediction Model Using Zero-İnflated Regression Approach. Theoretical and Applied Climatology, 137(1-2), 823-838. Lambert, D. (1992). Zero-Inflated Poisson Regression, With An Application To Defects In Manufacturing. Technometrics, 34(1), 1-14. Murat, Ö. Z. E. N. (2020). Kentsel Kavşaklarda Trafik Kazalarının Sıklığını Etkileyen Faktörlerin İncelenmesi. Teknik Dergi, 31(3). Miller, J., M., (2007). Comparing Poisson, Hurdle, And Zip Model Fit Under Varyıng Degrees Of Skew And Zero-Inflatıon. (Doktora Tezi) Unıversıty of Florida. Martin, T.G., Wintle, B.A., Rhodes, J.R., Kuhnert, P.M., Field, S.A., Low-Choy, S.J., Tyre, A.J. and Possingham, H.P. (2005). Zero Tolerance Ecology: Improving Ecological Inference by Modelling the Source of Zero Observations. EcologyLetters, 8 (11), 1235-1246. Pittman, B., Buta, E., Krishnan-Sarin, S., O’Malley, S. S., Liss, T., & Gueorguieva, R. (2018). Models for Analyzing Zero-Inflated and Overdispersed Count Data: An Application to Cigarette and Marijuana Use. Nicotine&TobaccoResearch. Peng, J. (2013). Count Data Models for Injury Data from the National Health Interview Survey, (M. Sc. Thesis), The Ohio State University Graduate Program in PublicHealth, Columbus. Ridout, M., Hinde, J. And Demetrio, C.G.B. (2001). A Score Test for a Zero-Inflated Poisson Regression Model Against Zero Inflated Negative Binomial Alternatives. Biometrics 57, 219-233. Sileshi, G., 2008. The Excess-Zero Problem In Soil Animal Count Data And Choice Of Appropriate Models For Statistical Inference. Pedobiologia. 52: 1-17. Sharma, A. K., & Landge, V. S. (2013). Zero İnflated Negative Binomial For Modeling Heavy Vehicle Crash Rate On Indian Rural Highway. International Journal of Advances in Engineering & Technology, 5(2), 292. Tüzel, Sema (2011). Hasar Sıklıkları İçin Sıfır Yığılmalı Kesikli Modeller. Yayınlanmış Yüksek lisans tezi. Hacettepe Üniversitesi Fen Bilimleri Enstitüsü, Ankara. Tüzen, M.F. and Erbaş, S. (2017). A Comparison Of Count Data Models With An Application To Daily Cigarette Consumption Of Young Persons. Communıcatıons In Statistics Theory And Methods, 1-20. Yang, Z., Hardin, J.W. and Addy, C. (2009). Testing Overdispersion in the Zero-Inflated Poisson Model. Journal of Statistics Planning and Inference, 139, 3340-3353. Yıldırım, G. (2019). Poisson Ve Negatif Binom Regresyon Modelleri. Yayınlanmış yüksek Lisans Tezi. Çukurova Üniversitesi, Fen Bilimleri Enstitüsü, Adana. Zhuo, L., Stacey, K., Lawrence, J. C., Lisa, K. H., Richard, H. L. M. O., (2008). Modeling Motor Vehicle Crashes For Street Racers Using Zero-Inflated Models. Accident Analysis and Prevention. 40: 835–839. Winkelmann, R. (2000). Econometric Analysis of Count Data (5th edition) Springer-Verlag Berlin Heidelberg. Wang, Z., Ma, S., & Wang, C. Y. (2015). Variable selection for zero‐inflated and overdispersed data with application to health care demand in Germany. Biometrical Journal, 57(5), 867-884.
Year 2020,
Volume: 46 Issue: 2, 85 - 102, 31.10.2020
Abstract
Bu çalışmada Türkiye için e-ticarette yaşanan sorun sayısına etki eden faktörlerin belirlenmesi amaçlanmıştır. Bu amaç doğrultusunda sayma veri modellerinden yararlanılmıştır. Uygulamada 2019 TÜİK hanehalkı bilişim teknolojileri kullanım anketinde yer alan sorun sayısı verilerine Poisson (P), negatif binom (NB), sıfır yığılmalı Poisson (ZIP), sıfır yığılmalı negatif binom (ZINB), Poisson Hurdle (PH) ve negatif binom Hurdle (NBH) regresyon modelleri uygulanmıştır. Bu modellerden hangi modelin veri setini daha iyi temsil ettiği Akaike Bilgi Kriteri, log olabilirlik, Vuong, Rootogram uyum iyiliği testleri kullanılarak karar verilmiştir. Analiz sonucuna göre ZINB modelinin tercih edilmesi gerektiği görülmüştür. Ayrıca ZINB modeline ait parametreler incelenmiş ve yorumlanmıştır.
References
- Açıkyürek, Gizem. (2016). Poisson Regresyon ve Bir Uygulama. Yayınlanmış Yüksek Lisans Tezi. Hacettepe Üniversitesi, Fen Bilimleri Enstitüsü, Ankara. Agresti, A. (2002). Categorical Data Analysis (Second Edition), New Jersey: Wiley & Sons Incorporation. Altun, E. (2018). A New Zero-Inflated Regression Model With Application. İstatistikçiler Dergisi: İstatistik ve Aktüerya, 11(2), 73-80. Asrul A.A.M. and Naingb, N.N. (2012). Analysis Death Rate of Age Model with Excess Zeros using Zero Inflated Negative Binomial and Negative Binomial Death Rate: Mortality AIDS Co-Infection Patients, Kelantan Malaysia. Procedia Economics and Finance, 2(2012), 275-283. Beaujean A.A. and Morgan G.B. (2016, February). Tutorial on Using Regression Models with Count Outcomes Using R. Practical Assessment Research & Evaluation, 21(2), 1531-7714. Cameron, A.C. and Trivedi, P.K. (2013). Regression Analysis of Count Data (Second Edition), New York: Cambridge University Press Carrivick, P.J.W., Lee, A.H. and Yau, K.K.W. (2003). Zero-inflated Poisson Modeling to Evaluate Occupational Safety Interventions. Safety Science, 41(1), 53-63. Canpolat, Ö. (2001). E-ticaret ve Türkiye'deki gelişmeler. Sanayi ve Ticaret Bakanlığı. ÇİLAN, Ç. A., & Sultan, K. U. Z. U. (2013). Kişisel E-Ticaret Uygulamalarının Kategorik Veri Analizi Yöntemleri İle Değerlendirilmesi. Alphanumeric Journal, 1(1), 27-32. Fang, R., (2013). Zero-Inflated Negative Binomial (ZINB) Regressıon Model for Over Dispersed Count Data with Excess Zeros and Repeated Measures an Application to Human Microbiota Sequence Data. Yüksek Lisans Tezi. Greene, W. H., 1994. Accounting For Excess Zeros And Sample Selection In Poisson And Negative Binomial Regression Models. New York University Department of Economics Working Paper , 94-10. Hilbe, J. M. (2014). Modelling Count Data (First Edition), New York: Cambridge University Press. Ismail, N., ve Zamani, H. (2013). Estimation Of Claimcount Data Using Negative Binomial, Generalized Poisson, Zero-İnflated Negative Binomial And Zero-İnflated Generalized Poisson Regression Models. In Casualty Actuarial Society E-Forum (Vol. 41, No. 20, pp. 1-28). İnternet: http://www.tuik.gov.tr/PreHaberBultenleri.do?id=30574 Kaya, Y., ve Yeşilova, A. (2012). E-Posta Trafiğinin Sıfır Değer Ağırlıklı Regresyon Yöntemleri Kullanılarak İncelenmesi. Anadolu University of Sciences & Technology-A: Applied Sciences & Engineering, 13(1). Karaca, A. G., ve Olmuş, H. (2018). Sıfır Değer Ağırlıklı Verilerin Analizinde Sıfır Değer Ağırlıklı Regresyon Modellerin İncelenmesi. Trakya Üniversitesi Sosyal Bilimler Dergisi, 20(2), 105-118. Karaca, A,. G. (2018). Sayma Verileri İçin Regresyon Modellerinin Karşılaştırılması Üzerine Bir Uygulama. Yayımlanmış Yüksek Lisans Tezi. Gazi Üniversitesi Fen Bilimleri Enstitüsü, Ankara. Kong, M., Xu, S., Levy, S.M. and Datta, S. (2014). “GEE Type Inference for Clustered Zero-Inflated Negative Binomial Regression with Application to Dental Caries”. Computational Statistics and Data Analysis, 85, 54-66. Kleiber, C., Zeileis, A., Visualizing Count Data Regressions using Rootograms. The American Statistician, 70(3), 296-303, 2016. Kim, D. W., Deo, R. C., Park, S. J., Lee, J. S., & Lee, W. S. (2019). Weekly Heat Wave Death Prediction Model Using Zero-İnflated Regression Approach. Theoretical and Applied Climatology, 137(1-2), 823-838. Lambert, D. (1992). Zero-Inflated Poisson Regression, With An Application To Defects In Manufacturing. Technometrics, 34(1), 1-14. Murat, Ö. Z. E. N. (2020). Kentsel Kavşaklarda Trafik Kazalarının Sıklığını Etkileyen Faktörlerin İncelenmesi. Teknik Dergi, 31(3). Miller, J., M., (2007). Comparing Poisson, Hurdle, And Zip Model Fit Under Varyıng Degrees Of Skew And Zero-Inflatıon. (Doktora Tezi) Unıversıty of Florida. Martin, T.G., Wintle, B.A., Rhodes, J.R., Kuhnert, P.M., Field, S.A., Low-Choy, S.J., Tyre, A.J. and Possingham, H.P. (2005). Zero Tolerance Ecology: Improving Ecological Inference by Modelling the Source of Zero Observations. EcologyLetters, 8 (11), 1235-1246. Pittman, B., Buta, E., Krishnan-Sarin, S., O’Malley, S. S., Liss, T., & Gueorguieva, R. (2018). Models for Analyzing Zero-Inflated and Overdispersed Count Data: An Application to Cigarette and Marijuana Use. Nicotine&TobaccoResearch. Peng, J. (2013). Count Data Models for Injury Data from the National Health Interview Survey, (M. Sc. Thesis), The Ohio State University Graduate Program in PublicHealth, Columbus. Ridout, M., Hinde, J. And Demetrio, C.G.B. (2001). A Score Test for a Zero-Inflated Poisson Regression Model Against Zero Inflated Negative Binomial Alternatives. Biometrics 57, 219-233. Sileshi, G., 2008. The Excess-Zero Problem In Soil Animal Count Data And Choice Of Appropriate Models For Statistical Inference. Pedobiologia. 52: 1-17. Sharma, A. K., & Landge, V. S. (2013). Zero İnflated Negative Binomial For Modeling Heavy Vehicle Crash Rate On Indian Rural Highway. International Journal of Advances in Engineering & Technology, 5(2), 292. Tüzel, Sema (2011). Hasar Sıklıkları İçin Sıfır Yığılmalı Kesikli Modeller. Yayınlanmış Yüksek lisans tezi. Hacettepe Üniversitesi Fen Bilimleri Enstitüsü, Ankara. Tüzen, M.F. and Erbaş, S. (2017). A Comparison Of Count Data Models With An Application To Daily Cigarette Consumption Of Young Persons. Communıcatıons In Statistics Theory And Methods, 1-20. Yang, Z., Hardin, J.W. and Addy, C. (2009). Testing Overdispersion in the Zero-Inflated Poisson Model. Journal of Statistics Planning and Inference, 139, 3340-3353. Yıldırım, G. (2019). Poisson Ve Negatif Binom Regresyon Modelleri. Yayınlanmış yüksek Lisans Tezi. Çukurova Üniversitesi, Fen Bilimleri Enstitüsü, Adana. Zhuo, L., Stacey, K., Lawrence, J. C., Lisa, K. H., Richard, H. L. M. O., (2008). Modeling Motor Vehicle Crashes For Street Racers Using Zero-Inflated Models. Accident Analysis and Prevention. 40: 835–839. Winkelmann, R. (2000). Econometric Analysis of Count Data (5th edition) Springer-Verlag Berlin Heidelberg. Wang, Z., Ma, S., & Wang, C. Y. (2015). Variable selection for zero‐inflated and overdispersed data with application to health care demand in Germany. Biometrical Journal, 57(5), 867-884.
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Details
| Primary Language | Turkish |
|---|---|
| Journal Section | Research Articles |
| Authors | |
| Publication Date | October 31, 2020 |
| Submission Date | May 29, 2020 |
| Published in Issue | Year 2020 Volume: 46 Issue: 2 |
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Journal Owner: On behalf of Selçuk University Faculty of Science, Rector Prof. Dr. Metin AKSOY
Selcuk University Journal of Science Faculty accepts articles in Turkish and English with original results in basic sciences and other applied sciences. The journal may also include compilations containing current innovations.
It was first published in 1981 as "S.Ü. Fen-Edebiyat Fakültesi Dergisi" and was published under this name until 1984 (Number 1-4).
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