A simple saddlepoint approximation for the equilibrium distribution of the stochastic logistic model of population growth

Abstract The deterministic logistic model of population growth and its notion of an equilibrium ‘carrying capacity’ are widely used in the ecological sciences. Leading texts also present a stochastic formulation of the model and discuss the concept and calculation of an equilibrium population size distribution. This paper describes a new method of finding accurate approximating distributions. Recently, cumulant approximations for the equilibrium distribution of this model were derived [Biometrics 52 (1996) 980], and separately a simple saddlepoint (SP) method of approximating distributions using exact cumulants was presented [J. Math. Appl. Med. Biol. 15 (1998) 41]. This paper proposed using the SP method with the new approximate cumulants, which are readily obtained from the assumed birth and death rates. The method is shown to be quite accurate with three test cases, namely on a classic model proposed by Pielou [Mathematical Ecology, New York, Wiley, p. 304] and on two African bee models proposed previously by the authors [Biometrics 52 (1996) 980; Theor. Popul. Biol. 53 (1998) 16]. Because the new method is also relatively simple to apply, it is expected that its use will lead to a more widespread utilization of the stochastic model in ecological modeling.

[1]  E. Renshaw,et al.  Applying the saddlepoint approximation to bivariate stochastic processes. , 2000, Mathematical biosciences.

[2]  Harold M. Hastings,et al.  Lack of predictability in model ecosystems based on coupled logistic equations , 1996 .

[3]  J. Matis,et al.  Use of birth-death-migration processes for describing the spread of insect populations , 1994 .

[4]  J. Matis,et al.  Effects of immigration on some stochastic logistic models: a cumulant truncation analysis. , 1999, Theoretical population biology.

[5]  Eric Renshaw Saddlepoint approximations for stochastic processes with truncated cumulant generating functions , 1998 .

[6]  M. Bartlett,et al.  A comparison of theoretical and empirical results for some stochastic population models , 1960 .

[7]  S. Huzurbazar Practical Saddlepoint Approximations , 1999 .

[8]  Eric Renshaw Modelling biological populations in space and time , 1990 .

[9]  George Casella,et al.  Explaining the Saddlepoint Approximation , 1999 .

[10]  J. Grasman,et al.  On local extinction in a metapopulation , 1997 .

[11]  A. W. Kemp,et al.  Univariate Discrete Distributions , 1993 .

[12]  H. Daniels Saddlepoint Approximations in Statistics , 1954 .

[13]  M. Makela,et al.  Invasive dynamics of africanized honeybees in North America , 1992, Naturwissenschaften.

[14]  James H. Matis,et al.  ON APPROXIMATING THE MOMENTS OF THE EQUILIBRIUM DISTRIBUTION OF A STOCHASTIC LOGISTIC MODEL , 1996 .

[15]  James H. Matis,et al.  Stochastic Population Models , 2000 .

[16]  Shih-Yu Wang General saddlepoint approximations in the bootstrap , 1992 .

[17]  R. Dilão,et al.  A general approach to the modelling of trophic chains , 1999, adap-org/9902002.

[18]  P. R. Parthasarathy,et al.  On the cumulants of population size for the stochastic power law logistic model. , 1998, Theoretical population biology.

[19]  H. E. Daniels,et al.  Tail Probability Approximations , 1987 .

[20]  S. Invernizzi,et al.  A generalized logistic model for photosynthetic growth , 1997 .