Research ArticleOpen AccessGoogle Scholar indexed
Estimation of Bounded Populations and Carrying Capacity with the Logistic Model
Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), Nairobi, Kenya
Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
- 1 Pan African University Institute for Basic Sciences, Technology and Innovation (PAUSTI), Nairobi, Kenya
- 2 Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya
Open Journal of Statistics·Volume 07 (2017)·Pages 936–943·Published 15 November 2017·DOI10.4236/ojs.2017.76065
Copy link · social · email
Abstract
Estimation of bounded populations and carrying capacity in the presence of a sample frame is considered. Models based on Logistic model are proposed. Like the existing estimators, this estimation technique deals with initial condition and is based on yearly population totals in order to fit in a model within a given period of time in this study. The proposed Logistic model technique has shown to be efficient especially with large data. The empirical study indicated that the Logistic model is efficient and can estimate properly even in the presence of outliers.
KeywordsLogistic ModelEstimationBounded PopulationCarrying CapacitySample FrameEmpirical Study and Outliers
- Edwards, C.H. and Penney, D.E. (2008) Differential Equations: Computing and Modeling. 4th Edition, 79-92.
- Hartley, H. and Ross, A. (1954) Unbiased Ratio Estimates. Nature, 174, 270-271. https://doi.org/10.1038/174270a0
- Al-Jararha, J. (2012) Unbiased Ratio Estimation for Finite Populations. LAMBERT Academic Publishing, Germany.
- Al-Jararha, J. and Al-Haj, E.M. (2012) A Ratio Estimator Under General Sampling Design. Austrian Journal of Statistics, 41, 105-115. https://doi.org/10.17713/ajs.v41i2.178
- Horvitz, D. and Thompson, D. (1952) A Generalization of Sampling without Replacement from a Finite Universe. Journal of the American Statistical Association, 47, 663-685. https://doi.org/10.1080/01621459.1952.10483446
- Olkin, I. (1958) Multivariate Ratio Estimation for the Finite Populations. Biometrika, 45, 154-165. https://doi.org/10.1093/biomet/45.1-2.154
- Singh, D. and Chaudhary, F. (1986) Theory and Analysis of Sample Survey Design. New Age Publication, New Delhi.
- Abu-Dayyeh, W., Ahmad, M., Ahmad, R. and Hassen, A. (2003) Some Estimators of a Finite Population Mean Using Auxiliary Information. Applied Mathematics and Computations, 139, 287-298. https://doi.org/10.1016/S0096-3003(02)00180-7
- Kadilar, C. and Cingi, H. (2004) Estimator of a Population Mean Using Two Auxiliary Variables in Simple Random Sampling. International Mathematical Journal, 5, 357-367.