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The Proposed Modified Schnute Model

Year 2024, Volume: 28 Issue: 2, 89 - 95, 23.08.2024
https://doi.org/10.19113/sdufenbed.1247670

Abstract

Büyüme verileri ile istatistiksel modelleme, daha objektif sonuçlar elde etmenin ve dahası büyümeyi anlamanın en etkili yoludur. Schnute büyüme modeli, birçok doğrusal olmayan büyüme modelini içeren büyük ölçekli bir model olup, özellikle büyüme eğrisinin asimptotik özellik taşıyıp taşımadığına bakılmaksızın, diğer büyüme modellerine göre optimum parametre tahminleri sunmaktadır.
Son yıllarda, literatür çalışmalarında, teorik ve uygulama alanlarında, büyüme denklemlerini anlamlandırmak için denklemlerin modifiye edildiği yaklaşımlar bulunmaktadır. Denklem modifikasyonunun amacı, büyüme parametrelerini, örneğin, maksimum değer, A; büyüme oranı ve gecikme süresi λ gibi anlamlı parametrelere dönüştürmektir.
Bu çalışmada, Schnute büyüme modeline ait parametrelerin hangi matematiksel işlemlerle anlamlı parametrelere dönüştürüldüğü gösterilmiş ve modifiye edilmiş yeni bir Schnute büyüme modeli literatüre sunulmuştur.

References

  • [1] Y. Akbaş, Büyüme Eğrisi Modellerinin Karşılaştırılması., Hayvansal Üretim. 36, 73-81, 1995, pp. 73-81.
  • [2] W. S. Kendal, Gompertzian Growth as a Consequence of Tumor Heterogeneity., Mathematical Biosciences, 73(1): 103-107., 1985.
  • [3] Gilligan C. A., Mathematical Modeling and Analysis of Soilborne Pathogens. In Epidemics of Plant Diseases:, Mathematical Analysis and Modeling, Heidelberg, Germany: Springer-Verlag, 96–142., 1990.
  • [4] Brown, J. E., Fitzhugh Jr, H. A., & Cartwright, T. C. (1976). A comparison of nonlinear models for describing weight-age relationships in cattle. Journal of Animal Science, 42(4), 810-818.
  • [5] A.M. Kshirsagar, W.B. Smish, Growth Curves., Marcel Dekker, Inc., 1-57., 1995.
  • [6] Trenkle, A., & Marple, D. N. (1983). Growth and development of meat animals. Journal of Animal Science, 57(suppl_2), 273-283.
  • [7] Owens, F. N., Dubeski, P., & Hanson, C. F. (1993). Factors that alter the growth and development of ruminants. Journal of animal science, 71(11), 3138-3150.
  • [8] M. E. Tıraşın, Balık Popülasyonlarının Büyüme Parametrelerinin Araştırılması., Doğa – Tr. J. of Zoology 17, 29-TÜBİTAK., 1993.
  • [9] Bredenkamp, B. V., & Gregoire, T. G. (1988). A forestry application of Schnute's generalized growth function. Forest science, 34(3), 790-797.
  • [10] v. L. Bertalanffy, Quantitative Laws in Metabolism and Growth., The University of Chicago Press, The Quarterly Review of Biology, 32(3): 217-231., 1957.
  • [11] J. F. Richards, A Flexible Growth Function for Empirical Use., Journal of Experimental Botany, 10 (29): 290-300 Published by: Oxford University Press., 1959.
  • [12] Yamada, S., Ohba, M., & Osaki, S. (1983). S-shaped reliability growth modeling for software error detection. IEEE Transactions on reliability, 32(5), 475-484..
  • [13] L. Taylor, A stagnationist model of economic growth., Cambridge Journal of Economics, 9(4), 383-403., 1985.
  • [14] Yang, Y., Doğan, O., & Taspinar, S. (2022). Model selection and model averaging for matrix exponential spatial models. Econometric Reviews, 41(8), 827-858.
  • [15] Ridley, D., & Llaugel, F. (2022). Generalized Four-Dimensional Scientific CDR Economic Growth Model: Expected Value, Average, and Limits to Growth. Theoretical Economics Letters, 12(3), 924-943.
  • [16] N. Kaldor, A model of economic growth., The economic journal, 67(268), 591-624., 1957.
  • [17] Perotto, D., Cue, R. I., & Lee, A. J. (1992). Comparison of nonlinear functions for describing the growth curve of three genotypes of dairy cattle. Canadian Journal of Animal Science, 72(4), 773-782.
  • [18] K. J. Vanclay, Modelling Forest Growth and Yield., Cab International, Wallingford, ISBN 0851989136, 312p., 1994.
  • [19] Fekedulegn, D., Mac Siúrtáin, M. P., & Colbert, J. J. (1999). Parameter Estimation of Nonlinear Models in Forestry. Silva Fennica, 33(4), 327-336.
  • [20] Bilgin, Ö. C., & Esenbuğa, N. (2003). Doğrusal-olmayan büyüme modellerinde parametre tahmini. Hayvansal Üretim, 44(2).
  • [21] Draper, N. R., & Smith, H. (1998). Applied regression analysis (Vol. 326). John Wiley & Sons.
  • [22] D. Marquardt, An Algorithm for Least Squares Estimation of Nonlinear Parameters., Journal of the Society of Industrial Applied Mathematics 2: 431–441., 1963.
  • [23] D. A. Ratkowsky, Nonlinear Regression Modelling, Marcel Dekker, Inc., New York. 276p., 1983.
  • [24] A. Ratkowsky D, Handbook of Nonlinear Regression., New York: Marcel Dekker, Inc., 1990.
  • [25] N. L. Bowers, H. Gerber, J. Hiskman, D. Jones ve C. Nesbitt, Actuarial Mathematics., Society of Actuaries. Schaumburg, IL 753., 1997.
  • [26] A. De Moivre, Miscellanea Analytica de Seriebus et Quadraturis., J. Tonson and J. Watts, London., 1730.
  • [27] B. Gompertz, On the Nature of the Function Expressive of the Law of Human Mortality and on a New Mode of Determining the Value of Life Contigencies., London Phil. Trans. Roy. Soc. 115: 513-585., 1825.
  • [28] S. Brody, Bioenergetics and Growth., Hafner, NewYork., 1945.
  • [29] Liang, T. C., & Balakrishnan, N. (1992). A characterization of exponential distributions through conditional independence. Journal of the Royal Statistical Society Series B: Statistical Methodology, 54(1), 269-271.
  • [30] J. Schnute, A Versatile Growth Model with Statistically Stable Parameters., Can. J. Fish. Aquat. Sci. 38: 1128-1140., 1981.
  • [31] W. M. Makeham, On the Law of Mortality and the Construction of Annuity Tables., J. Inst. Actuaries and Assur. Mag. 8(6): 301–310., 1860.
Year 2024, Volume: 28 Issue: 2, 89 - 95, 23.08.2024
https://doi.org/10.19113/sdufenbed.1247670

Abstract

References

  • [1] Y. Akbaş, Büyüme Eğrisi Modellerinin Karşılaştırılması., Hayvansal Üretim. 36, 73-81, 1995, pp. 73-81.
  • [2] W. S. Kendal, Gompertzian Growth as a Consequence of Tumor Heterogeneity., Mathematical Biosciences, 73(1): 103-107., 1985.
  • [3] Gilligan C. A., Mathematical Modeling and Analysis of Soilborne Pathogens. In Epidemics of Plant Diseases:, Mathematical Analysis and Modeling, Heidelberg, Germany: Springer-Verlag, 96–142., 1990.
  • [4] Brown, J. E., Fitzhugh Jr, H. A., & Cartwright, T. C. (1976). A comparison of nonlinear models for describing weight-age relationships in cattle. Journal of Animal Science, 42(4), 810-818.
  • [5] A.M. Kshirsagar, W.B. Smish, Growth Curves., Marcel Dekker, Inc., 1-57., 1995.
  • [6] Trenkle, A., & Marple, D. N. (1983). Growth and development of meat animals. Journal of Animal Science, 57(suppl_2), 273-283.
  • [7] Owens, F. N., Dubeski, P., & Hanson, C. F. (1993). Factors that alter the growth and development of ruminants. Journal of animal science, 71(11), 3138-3150.
  • [8] M. E. Tıraşın, Balık Popülasyonlarının Büyüme Parametrelerinin Araştırılması., Doğa – Tr. J. of Zoology 17, 29-TÜBİTAK., 1993.
  • [9] Bredenkamp, B. V., & Gregoire, T. G. (1988). A forestry application of Schnute's generalized growth function. Forest science, 34(3), 790-797.
  • [10] v. L. Bertalanffy, Quantitative Laws in Metabolism and Growth., The University of Chicago Press, The Quarterly Review of Biology, 32(3): 217-231., 1957.
  • [11] J. F. Richards, A Flexible Growth Function for Empirical Use., Journal of Experimental Botany, 10 (29): 290-300 Published by: Oxford University Press., 1959.
  • [12] Yamada, S., Ohba, M., & Osaki, S. (1983). S-shaped reliability growth modeling for software error detection. IEEE Transactions on reliability, 32(5), 475-484..
  • [13] L. Taylor, A stagnationist model of economic growth., Cambridge Journal of Economics, 9(4), 383-403., 1985.
  • [14] Yang, Y., Doğan, O., & Taspinar, S. (2022). Model selection and model averaging for matrix exponential spatial models. Econometric Reviews, 41(8), 827-858.
  • [15] Ridley, D., & Llaugel, F. (2022). Generalized Four-Dimensional Scientific CDR Economic Growth Model: Expected Value, Average, and Limits to Growth. Theoretical Economics Letters, 12(3), 924-943.
  • [16] N. Kaldor, A model of economic growth., The economic journal, 67(268), 591-624., 1957.
  • [17] Perotto, D., Cue, R. I., & Lee, A. J. (1992). Comparison of nonlinear functions for describing the growth curve of three genotypes of dairy cattle. Canadian Journal of Animal Science, 72(4), 773-782.
  • [18] K. J. Vanclay, Modelling Forest Growth and Yield., Cab International, Wallingford, ISBN 0851989136, 312p., 1994.
  • [19] Fekedulegn, D., Mac Siúrtáin, M. P., & Colbert, J. J. (1999). Parameter Estimation of Nonlinear Models in Forestry. Silva Fennica, 33(4), 327-336.
  • [20] Bilgin, Ö. C., & Esenbuğa, N. (2003). Doğrusal-olmayan büyüme modellerinde parametre tahmini. Hayvansal Üretim, 44(2).
  • [21] Draper, N. R., & Smith, H. (1998). Applied regression analysis (Vol. 326). John Wiley & Sons.
  • [22] D. Marquardt, An Algorithm for Least Squares Estimation of Nonlinear Parameters., Journal of the Society of Industrial Applied Mathematics 2: 431–441., 1963.
  • [23] D. A. Ratkowsky, Nonlinear Regression Modelling, Marcel Dekker, Inc., New York. 276p., 1983.
  • [24] A. Ratkowsky D, Handbook of Nonlinear Regression., New York: Marcel Dekker, Inc., 1990.
  • [25] N. L. Bowers, H. Gerber, J. Hiskman, D. Jones ve C. Nesbitt, Actuarial Mathematics., Society of Actuaries. Schaumburg, IL 753., 1997.
  • [26] A. De Moivre, Miscellanea Analytica de Seriebus et Quadraturis., J. Tonson and J. Watts, London., 1730.
  • [27] B. Gompertz, On the Nature of the Function Expressive of the Law of Human Mortality and on a New Mode of Determining the Value of Life Contigencies., London Phil. Trans. Roy. Soc. 115: 513-585., 1825.
  • [28] S. Brody, Bioenergetics and Growth., Hafner, NewYork., 1945.
  • [29] Liang, T. C., & Balakrishnan, N. (1992). A characterization of exponential distributions through conditional independence. Journal of the Royal Statistical Society Series B: Statistical Methodology, 54(1), 269-271.
  • [30] J. Schnute, A Versatile Growth Model with Statistically Stable Parameters., Can. J. Fish. Aquat. Sci. 38: 1128-1140., 1981.
  • [31] W. M. Makeham, On the Law of Mortality and the Construction of Annuity Tables., J. Inst. Actuaries and Assur. Mag. 8(6): 301–310., 1860.
There are 31 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Olgun Duran 0000-0002-5492-6795

Deniz Ünal 0000-0002-4095-3039

Publication Date August 23, 2024
Published in Issue Year 2024 Volume: 28 Issue: 2

Cite

APA Duran, O., & Ünal, D. (2024). The Proposed Modified Schnute Model. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 28(2), 89-95. https://doi.org/10.19113/sdufenbed.1247670
AMA Duran O, Ünal D. The Proposed Modified Schnute Model. J. Nat. Appl. Sci. August 2024;28(2):89-95. doi:10.19113/sdufenbed.1247670
Chicago Duran, Olgun, and Deniz Ünal. “The Proposed Modified Schnute Model”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 28, no. 2 (August 2024): 89-95. https://doi.org/10.19113/sdufenbed.1247670.
EndNote Duran O, Ünal D (August 1, 2024) The Proposed Modified Schnute Model. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 28 2 89–95.
IEEE O. Duran and D. Ünal, “The Proposed Modified Schnute Model”, J. Nat. Appl. Sci., vol. 28, no. 2, pp. 89–95, 2024, doi: 10.19113/sdufenbed.1247670.
ISNAD Duran, Olgun - Ünal, Deniz. “The Proposed Modified Schnute Model”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi 28/2 (August 2024), 89-95. https://doi.org/10.19113/sdufenbed.1247670.
JAMA Duran O, Ünal D. The Proposed Modified Schnute Model. J. Nat. Appl. Sci. 2024;28:89–95.
MLA Duran, Olgun and Deniz Ünal. “The Proposed Modified Schnute Model”. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 28, no. 2, 2024, pp. 89-95, doi:10.19113/sdufenbed.1247670.
Vancouver Duran O, Ünal D. The Proposed Modified Schnute Model. J. Nat. Appl. Sci. 2024;28(2):89-95.

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