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1 April 2000 Statistical Inference on Associated Fertility Life Parameters Using Jackknife Technique: Computational Aspects
Aline de H. N. Maia, Alfredo J. B. Luiz, Clayton Campanhola
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Abstract

Knowledge of population growth potential is crucial for studying population dynamics and for establishing management tactics for pest control. Estimation of population growth can be achieved with fertility life tables because they synthesize data on reproduction and mortality of a population. The five main parameters associated with a fertility life table are as follows: (1) the net reproductive rate (Ro), (2) the intrinsic rate of increase (rm), 3) the mean generation time (T), (4) the doubling time (Dt), and (5) the finite rate of increase (λ). Jackknife and bootstrap techniques are used to calculate the variance of the rm estimate, which can be extended to the other parameters of life tables. Those methods are computer-intensive, their application requires the development of efficient algorithms, and their implementation is based on a programming language that encompasses quickness and reliability. The objectives of this article are to discuss statistical and computational aspects related to estimation of life table parameters and to present a SAS program that uses jackknife to estimate parameters for fertility life tables. The SAS program presented here allows the calculation of confidence intervals for all estimated parameters, as well as provides one-sided and two-sided t-tests to perform pairwise or multiple comparison between groups, with their respective P values.

Aline de H. N. Maia, Alfredo J. B. Luiz, and Clayton Campanhola "Statistical Inference on Associated Fertility Life Parameters Using Jackknife Technique: Computational Aspects," Journal of Economic Entomology 93(2), 511-518, (1 April 2000). https://doi.org/10.1603/0022-0493-93.2.511
Received: 8 February 1999; Accepted: 1 December 1999; Published: 1 April 2000
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KEYWORDS
Computer program
fertility life tables
intrinsic rate of increase
jackknife technique
SAS program
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