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Radiation Risk Estimation: Based on Measurement Error Models de Sergii Masiuk

Radiation Risk Estimation: Based on Measurement Error Models: De Gruyter Series in Mathematics and Life Sciences, cartea 5

Autor Sergii Masiuk, Alexander Kukush, Sergiy Shklyar, Mykola Chepurny, Illya Likhtarov
en Limba Engleză Electronic book text – 5 mar 2017
This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.
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Specificații

ISBN-13: 9783110433470
ISBN-10: 3110433478
Pagini: 270
Ilustrații: 13 schw.-w. u. 1 farb. Abb., 7 farb. Tab.
Editura: De Gruyter
Colecția De Gruyter
Seria De Gruyter Series in Mathematics and Life Sciences

Locul publicării:Berlin/Boston

Notă biografică

S. Masiuk, A. Kukush, S. Shklyar, M. Chepurny, I. Likhtarov, Radiation Protection Institute, Ukraine.

Descriere

The De Gruyter Series in Mathematics and Life Sciences is devoted to the publication of monographs in the field. They cover topics and methods in fields of current interest that use mathematical approaches to understand and explain, model and influence phenomena in all areas of life sciences. This includes, among others, theory and application of biological mathematical modeling, complex systems biology, bioinformatics, computational biomodeling stochastic modeling, biostatistics, computational evolutionary biology, comparative genomics, or structural bioinformatics. Also, new types of mathematical problems shall be covered that arise from biological knowledge.
The main objectives is to make such expositions available to and accessible by an interdisciplinary, growing readership hailing from all disciplines involved. The volumes shall convey the context of the given topic and enable these readers to understand, apply and develop further mathematical methods to given problems in biology. For this reason, works with up to four authors are preferred over edited volumes.
Therefore, contributions which are on the borderline of mathematics and life sciences and which stimulate further research at the crossroads of these areas are particularly welcome. In addition, use of electronic media to demonstrate, visualize and model the methods presented are very welcome, especially when interwoven with the written text.