Literature DB >> 4023951

Confidence intervals for demographic projections based on products of random matrices.

C C Heyde, J E Cohen.   

Abstract

This work is concerned with the growth of age-structured populations whose vital rates vary stochastically in time and with the provision of confidence intervals. In this paper a model Yt + 1(omega) = Xt + 1(omega) Yt(omega) is considered, where Yt is the (column) vector of the numbers of individuals in each age class at time t, X is a matrix of vital rates, and omega refers to a particular realization of the process that produces the vital rates. It is assumed that (Xi) is a stationary sequence of random matrices with nonnegative elements and that there is an integer n0 such that any product Xj + n0...Xj + 1Xj has all its elements positive with probability one. Then, under mild additional conditions, strong laws of large numbers and central limit results are obtained for the logarithms of the components of Yt. Large-sample estimators of the parameters in these limit results are derived. From these, confidence intervals on population growth and growth rates can be constructed. Various finite-sample estimators are studied numerically. The estimators are then used to study the growth of the striped bass population breeding in the Potomac River of the eastern United States.

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Year:  1985        PMID: 4023951     DOI: 10.1016/0040-5809(85)90007-3

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  7 in total

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Authors:  Richard R Lawler; Hal Caswell; Alison F Richard; Joelisoa Ratsirarson; Robert E Dewar; Marion Schwartz
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3.  Extinction dynamics of age-structured populations in a fluctuating environment.

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4.  Population forecasts and confidence intervals for Sweden: a comparison of model-based and empirical approaches.

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5.  Demography in stochastic environments. II. Growth and convergence rates.

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6.  Estimating the time to extinction in an island population of song sparrows.

Authors:  B E Saether; S Engen; R Lande; P Arcese; J N Smith
Journal:  Proc Biol Sci       Date:  2000-03-22       Impact factor: 5.349

7.  Population resistance to climate change: modelling the effects of low recruitment in open populations.

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  7 in total

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