Öz
Besi sığırı performansını ve karlılığını etkileyen birkaç değişken vardır. İlgili literatürde, farklı yönetim sistemlerinde karlılığı etkileyen değişkenlerin katkısını bulmak için regresyon analizi kullanılmıştır. Regresyon analizinde çoğunlukla en küçük kareler (LS) tahmin yöntemi kullanılır. Ancak, bu yöntem hata terimlerinin dağılımının normal olması durumunda optimaldir. Bu çalışmada, normallik varsayımı altında regresyon analizinin kullanıldığı Koknaroğlu ve ark. (2005) çalışması revize edilmiştir. Shapiro-Wilk normallik testine göre hata terimleri için normallik varsayımını sağlanmadığından, diğer çalışmadan farklı olarak, bu çalışmada, M-tahmini adı verilen dayanıklı/robust tahmin yöntemi kullanılmıştır. Belirleme katsayısı ile birlikte parametre tahminleri ve onların standart hataları elde edilmiştir. Sonuç olarak, 𝑅2 kriterine göre, M-tahminine dayalı olarak elde edilen sonuçların, LS tahmin edicilerinden daha güvenilir olduğu gözlenmiştir.
Anahtar Kelimeler
Kaynakça
- Acitas, S., Kasap, P., Senoglu, B., Arslan, O., 2013a. Robust estimation with the skew t2 distribution. Pakistan Journal of Statistics, 29(4): 409-430.
- Acitas, S., Kasap, P., Senoglu, B., Arslan, O., 2013b. One-step M-estimators: Jones and Faddy's skewed t-distribution. Journal of Applied Statistics, 40(7): 1545-1560.
- Acitas, S., Senoglu, B., 2018. Iran J Sci Technol Trans Sci https://doi.org/10.1007/s40995-018-0528-6.
- Geary, R. C., 1947. Testing for normality. Biometrika, 34(3/4): 209-242.
- Huber, P. J., 1964. Robust estimation of a location parameter. The annals of mathematical statistics, 35(1): 73-101.
- Huber, P. J., 1981. Robust statistics. Wiley.
- Islam, M. Q., Tiku, M. L., 2005. Multiple linear regression model under nonnormality. Communications in Statistics-Theory and Methods, 33(10): 2443-2467.
- Jureckova, J., Picek, J., 2005. Robust statistical methods with R. Chapman and Hall/CRC.
- Koknaroglu, H., Loy, D. D., Wilson, D. E., Hoffman, M. P., Lawrence, J. D., 2005. Factors affecting beef cattle performance and profitability. The Professional Animal Scientist, 21(4): 286-296.
- Koknaroglu, H., Turan, C., Toker, M. T., 2008. Animal science application of robust tests: effect of zeolite and initial weight on fattening performance of cattle. Animal Science Papers and Reports, 26(2): 107-115.
- Maronna, R. A. R. D., Martin, R. D., & Yohai, V., 2006. Robust statistics. John Wiley & Sons.
- Montgomery, D. C., Peck, E. A., Vining, G. G., 2012. Introduction to linear regression analysis. John Wiley & Sons.
- Oner, M., Deveci Kocakoc, I., 2017. JMASM 49: A Compilation of Some Popular Goodness of Fit Tests for Normal Distribution: Their Algorithms and MATLAB Codes (MATLAB). Journal of Modern Applied Statistical Methods, 16(2): 547-575.
- Renaud, O., Victoria-Feser, M. P., 2010. A robust coefficient of determination for regression. Journal of Statistical Planning and Inference, 140(7): 1852-1862.
- Rousseeuw, P. J., 1984. Least median of squares regression. Journal of the American Statistical Association, 79: 871–880.
- Shapiro, S. S., Wilk, M. B., 1965. An analysis of variance test for normality (complete samples). Biometrika, 52(3/4): 591-611.
- Senoglu, B., 2005. Robust 2^k factorial design with Weibull error distributions. Journal of Applied Statistics, 32(10): 1051-1066.
- Tiku, M. L., 1967. Estimating the mean and standard deviation from a censored normal sample. Biometrika, 54: 155-165.
- Tiku, M. L., 1968. Estimating the parameters of normal and logistic distributions from censored samples. Australian & New Zealand Journal of Statistics, 10(2): 64-74.
- Yohai, V. J., 1987. High breakdown-point and high efficiency robust estimates for regression. The Annals of Statistics, 15: 642-656.
Öz
There are several variables affecting the beef cattle performance and profitability. In the related literature, regression analysis is performed to find the contribution of the variables on profitability in different managing systems. Least squares (LS) estimation method is mostly used in regression analysis. However, it is optimal when the distribution of the error terms is normal. In this study, we revise Koknaroglu et al. (2005) study in which regression analysis is used under normality assumption. Different from the mentioned study, we use a robust estimation method called M-estimation since the error terms do not follow a normal distribution according to Shapiro-Wilk normality test. We obtain parameter estimates and their standard errors along with the coefficient of determination. It is observed that the results obtained based on M-estimation are more reliable than their LS counterparts with respect to 𝑅2 criterion.
Anahtar Kelimeler
Beef cattle Profitability Regression Robustness M-estimation
Kaynakça
- Acitas, S., Kasap, P., Senoglu, B., Arslan, O., 2013a. Robust estimation with the skew t2 distribution. Pakistan Journal of Statistics, 29(4): 409-430.
- Acitas, S., Kasap, P., Senoglu, B., Arslan, O., 2013b. One-step M-estimators: Jones and Faddy's skewed t-distribution. Journal of Applied Statistics, 40(7): 1545-1560.
- Acitas, S., Senoglu, B., 2018. Iran J Sci Technol Trans Sci https://doi.org/10.1007/s40995-018-0528-6.
- Geary, R. C., 1947. Testing for normality. Biometrika, 34(3/4): 209-242.
- Huber, P. J., 1964. Robust estimation of a location parameter. The annals of mathematical statistics, 35(1): 73-101.
- Huber, P. J., 1981. Robust statistics. Wiley.
- Islam, M. Q., Tiku, M. L., 2005. Multiple linear regression model under nonnormality. Communications in Statistics-Theory and Methods, 33(10): 2443-2467.
- Jureckova, J., Picek, J., 2005. Robust statistical methods with R. Chapman and Hall/CRC.
- Koknaroglu, H., Loy, D. D., Wilson, D. E., Hoffman, M. P., Lawrence, J. D., 2005. Factors affecting beef cattle performance and profitability. The Professional Animal Scientist, 21(4): 286-296.
- Koknaroglu, H., Turan, C., Toker, M. T., 2008. Animal science application of robust tests: effect of zeolite and initial weight on fattening performance of cattle. Animal Science Papers and Reports, 26(2): 107-115.
- Maronna, R. A. R. D., Martin, R. D., & Yohai, V., 2006. Robust statistics. John Wiley & Sons.
- Montgomery, D. C., Peck, E. A., Vining, G. G., 2012. Introduction to linear regression analysis. John Wiley & Sons.
- Oner, M., Deveci Kocakoc, I., 2017. JMASM 49: A Compilation of Some Popular Goodness of Fit Tests for Normal Distribution: Their Algorithms and MATLAB Codes (MATLAB). Journal of Modern Applied Statistical Methods, 16(2): 547-575.
- Renaud, O., Victoria-Feser, M. P., 2010. A robust coefficient of determination for regression. Journal of Statistical Planning and Inference, 140(7): 1852-1862.
- Rousseeuw, P. J., 1984. Least median of squares regression. Journal of the American Statistical Association, 79: 871–880.
- Shapiro, S. S., Wilk, M. B., 1965. An analysis of variance test for normality (complete samples). Biometrika, 52(3/4): 591-611.
- Senoglu, B., 2005. Robust 2^k factorial design with Weibull error distributions. Journal of Applied Statistics, 32(10): 1051-1066.
- Tiku, M. L., 1967. Estimating the mean and standard deviation from a censored normal sample. Biometrika, 54: 155-165.
- Tiku, M. L., 1968. Estimating the parameters of normal and logistic distributions from censored samples. Australian & New Zealand Journal of Statistics, 10(2): 64-74.
- Yohai, V. J., 1987. High breakdown-point and high efficiency robust estimates for regression. The Annals of Statistics, 15: 642-656.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Ziraat, Veterinerlik ve Gıda Bilimleri, Hayvansal Üretim (Diğer) |
| Bölüm | Araştırma Makaleleri |
| Yazarlar | |
| Yayımlanma Tarihi | 19 Eylül 2019 |
| Gönderilme Tarihi | 28 Aralık 2018 |
| Yayımlandığı Sayı | Yıl 2019 Cilt: 23 Sayı: 3 |
Derginin Tarandığı İndeksler
Harran Tarım ve Gıda Bilimi Dergisi, Creative Commons Atıf –Gayrı Ticari 4.0 Uluslararası (CC BY-NC 4.0) Lisansı ile lisanslanmıştır.