Biswas, Suddhendu; Ebraheem, Nather Abas On an application of the diffusion approximation of the generalized birth and death process for stochastic population projection. (English) Zbl 0645.92018 Commun. Stat., Theory Methods 17, No. 3, 779-789 (1988). Assuming that both birth and death rates are density and time dependent, a diffusion approximation of the generalized birth and death process has been considered in this paper to obtain a suitable stochastic population model describing the population size and its moments. A simple method of estimating the parameters of the model is discussed. The predictions of the expected size of the population, and the variance are made and compared with the corresponding census figures as well as with another deterministic projection series made for the corresponding period. Cited in 1 Document MSC: 92D25 Population dynamics (general) 60J85 Applications of branching processes Keywords:density dependent; logistic population; time dependent; diffusion approximation; generalized birth and death process; stochastic population model; population size; moments; deterministic projection PDFBibTeX XMLCite \textit{S. Biswas} and \textit{N. A. Ebraheem}, Commun. Stat., Theory Methods 17, No. 3, 779--789 (1988; Zbl 0645.92018) Full Text: DOI References: [1] Ambannavar J.P., Long Term prospects of population growth and labour force in India (1975) [2] Biswas S., Journal of Management Science and Applied Cybernatics 15 pp 90– (1986) [3] Biswas S., Demography India 16 pp 119– (1987) [4] Biswas S., Communivated for publication (1987) [5] DOI: 10.1093/biomet/33.3.183 · Zbl 0060.31803 · doi:10.1093/biomet/33.3.183 [6] Leslie P.H., Biometrika 35 pp 213– (1948) [7] Nisbet R.M., Modelling fluctuating Populations (1982) · Zbl 0593.92013 [8] 1985.Sample Registration, XIX(2) December [9] Census of India (1981) This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.