Power of Parametric and Semi-parametric Models to Represent Real Life Data Situations

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概要

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• Real-life data situations are not easy to model because of the uncertainty and variation prevailing in the natural system and also due to the presence of the interaction of unknown factors interplaying and governing the entire real-life phenomena. Modelling fish dynamics has been considered as an indispensable area of research by the biologists, bioresearchers, applied and bio-mathematicians to understand the science behind the growth of fish. Valuable contributions in this area are available in different monographs, books and journals. The models prevalent for use are, generally, of two types - deterministic and non-deterministic. The celebrated Von Bertalanffy (VB) model, fitted deterministically, is the main thurst area of research till now to the active biology-modellers and is also considered as the most appropriate one. Non-deterministic models are widely applicable for their inherent capability to provide better representations owing to the fact that these imbibe elements of uncertainty inbuilt in their systems of operation. Efforts in this area call upon using a log transformation on a relationship representing an exponential relationship between the variables, weight and length of fish. The object of data modelling is to generate fitted values as close as possible to the observed values. Longitudinal data modelling can be achieved by parametric and nonparametric modelling. Deterministic fitting of VB equation ensures achieving precision (desired closeness) only up to a certain degree of precision. Precise modular representation of such data comes as a useful complement. This paper deals with non-linear fit (achieved through non-linear optimization), a parametric approach, of the VB model. Also introduced here is the application of distribution free approach, like, nonparametric model fitting, which does not involve parameters (which need to be estimated from the data). Such models assign more importance to data points and the span of the regions surrounding those. This paper exposes the power (in respec

• 広島大学の論文
• 2005-03-28

著者

• 景山 三平

  広島大学学校教育学部

• 景山 三平

  広島大学大学院教育学研究科

• Medda C

  Indian Statistical Institute

• Pal Satyabrata

  Bidhan Chandra Krishi Viswavidyalaya

• Pal Subhabaha

  University of Calcutta, Ballygunge Campus

• Basu T.

  Indian Statistical Institute

• Pal Satyabrata

  Bidhan Chandra Agricultural University

• Basu T

  Indian Statistical Institute

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