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Stage-Structured Populations: Sampling, analysis and simulation (Molecular Biology Intelligence Unit) ePub download

by Bryan F.J. Manly

  • Author: Bryan F.J. Manly
  • ISBN: 0412350602
  • ISBN13: 978-0412350603
  • ePub: 1648 kb | FB2: 1785 kb
  • Language: English
  • Category: Science & Mathematics
  • Publisher: Springer; 1990 edition (December 14, 1989)
  • Pages: 187
  • Rating: 4.8/5
  • Votes: 506
  • Format: doc rtf lrf lrf
Stage-Structured Populations: Sampling, analysis and simulation (Molecular Biology Intelligence Unit) ePub download

Sampling, analysis and simulation. Authors: Manly, Bryan .

Sampling, analysis and simulation. The topics covered are sam­ pling designs (Chapter 2), the estimation of parameters by maximum likelihood (Chapter 3), the analysis of sample counts of the numbers cif individuals in different stages at different times (Chapters 4 and 5), the analysis of data using Leslie matrix types of model (Chapter 6) and key factor analysis (Chapter 7). There.

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Stage-Structured Populations : Sampling, Analysis and Simulation.

Stage-Structured Populations: Sampling, Analysis and Simulation. A Modern Course on Statistical Distributions in Scientific Work. A model for the analysis of insect stage-frequency data is developed which includes stage-specific variable developmental periods and stage-specific daily survival rates. The model can predict the development of an insect population through its developmental stages and consequently may form the basis for a simulation model of the population. A new method is proposed for detecting key factors from life tables for animals whose life-cycle is divided into several stages.

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The rst serious molecular Monte Carlo simulation appeared in 1953, closely followed .

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This book provides a review of methods for obtaining and analysing data from stage-structured biological populations. The topics covered are sam­ pling designs (Chapter 2), the estimation of parameters by maximum likelihood (Chapter 3), the analysis of sample counts of the numbers cif individuals in different stages at different times (Chapters 4 and 5), the analysis of data using Leslie matrix types of model (Chapter 6) and key factor analysis (Chapter 7). There is also some discussion of the approaches to modelling and estimation that have been used in five studies of particular populations (Chapter 8). There is a large literature on the modelling of biological populations, and a multitude of different approaches have been used in this area. The various approaches can be classified in different ways (Southwood, 1978, ch. 12), but for the purposes of this book it is convenient to think of the three categories mathematical, statistical and predictive modelling. Mathematical modelling is concerned largely with developing models that capture the most important qualitative features of population dynamics. In this case, the models that are developed do not have to be compared with data from natural populations. As representations of idealized systems, they can be quite informative in showing the effects of changing parameters, indicating what factors are most important in promoting stability, and so on.
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