Otwarty dostęp

Johnson–Schumacher Split-Plot Design Modelling of Rice Yield


Zacytuj

Almimi A.A., Kulahci M., Montgomery D.C. (2006): Checking the adequacy of fit of models from split-plot designs. Journal of Quality Technology 38: 58–190. Search in Google Scholar

Anderson M.J. (2016): Design of Experiments (DoE): How to handle hard-to-change factors using a split plot. Chemical Engineering, 123(9): 12-1-12-5. Search in Google Scholar

Bates D.M., Watts D.G. (1988): Nonlinear Regression Analysis and Its Applications, New York: Wiley. Search in Google Scholar

Blankenship E.E., Stroup W.W., Evans S.P., Knezevic S.Z. (2003): Statistical Inference for Calibration Points in Nonlinear Mixed Effects Models. American Statistical Association and the International Biometric Society Journal of Agricultural, Biological, and Environmental Statistics, 8(4): 455–468. Search in Google Scholar

David I.J., Adubisi O.D., Ogbaji O.E., Eghwerido J.T., Umar Z.A. (2020): Resistant measures in assessing the adequacy of regression models. Scientific African, 8, e00437. https://doi.org/10.1016/j.sciaf.2020.e00437 Search in Google Scholar

David I.J., Asiribo O.E., Dikko H.G. (2016): Resistant Measures in Assessing the Adequacy of Split-plot Design Models. International Journal of Data Science, 1(4): 382–396. Search in Google Scholar

David I.J., Asiribo O.E., Dikko H.G. (2018): Nonlinear Split-Plot Design Model in Parameters Estimation using EGLS-MLE. ComTech: Computer, Mathematics and Engineering Applications, 9(2): 65–71. Search in Google Scholar

David I.J., Asiribo O.E., Dikko H.G. (2019): Parameter Estimation of Nonlinear Split-Plot Design Models: A Theoretical Framework. Journal of Reliability and Statistical Studies, 12(1): 117–129. Search in Google Scholar

David I.J., Asiribo O.E., Dikko H.G. (2022): A Bertalanffy-Richards Split-Plot Design Model and Analysis. Journal of Statistical Modeling and Analysis, 4(1): 56–71. Search in Google Scholar

David I.J., Asiribo O.E., Dikko H.G. (2022): A Weibull Split-Plot Design Model and Analysis. Thailand Statistician, 20(2): 420–434. Search in Google Scholar

David I.J., Asiribo O.E., Dikko H.G. (2023): Nonlinear split-plot design modeling and analysis of rice varieties yield. Scientific African, 19, e01444. Search in Google Scholar

Gumpertz M.L., Pantula S.G. (1992): Nonlinear Regression with Variance Components. Journal of the American Statistical Association, 87(417): 201–209. Search in Google Scholar

Gumpertz M.L., Rawlings J.O. (1992): Nonlinear Regression with Variance Components: Modeling Effects of Ozone on Crop Yield. Crop Science, 32: 219–224. Search in Google Scholar

Harville D.A. (1977): Maximum likelihood approaches to variance components estimation and to related problems. Journal of the American Statistical Association, 72: 320–338. Search in Google Scholar

Huameng G., Fan Y., Lei S. (2017): Split Plot and Data Analysis in SAS. American Institute of Physics Conference Proceedings 1834, 030024 (2017); doi:10.1063/1.4981589. Search in Google Scholar

Klotz J.H. (2006): A computational approach to statistics. Madison: University of Wisconsin. Search in Google Scholar

Knezevic S.Z., Evans S.P., Blankenship E.E., Van Acker R.C., Lindquist J.L. (2002): Critical period for weed control: the concept and data analysis. Agronomy – Faculty Publications. Paper 407. Search in Google Scholar

Kulachi M.A. Menon (2017): Trellis plots as visual aids for analyzing split plot experiments. Quality Engineering, 29(2): 211-225. https://doi.org/10.1080/08982112.2016.1243248 Search in Google Scholar

Kvalseth T.O. (1985): Cautionary note about R2. The American Statistician, 39: 279–285. Search in Google Scholar

eISSN:
2199-577X
Język:
Angielski
Częstotliwość wydawania:
2 razy w roku
Dziedziny czasopisma:
Life Sciences, Bioinformatics, other, Mathematics, Probability and Statistics, Applied Mathematics