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Titlebook: Optimal Mixture Experiments; B.K. Sinha,N.K. Mandal,P. Das Book 2014 Springer Nature India Private Limited 2014 Bayesian Analysis.Design o

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发表于 2025-3-21 16:59:55 | 显示全部楼层 |阅读模式
书目名称Optimal Mixture Experiments
编辑B.K. Sinha,N.K. Mandal,P. Das
视频video
概述Includes optimality consideration for estimating both linear and non-linear functions of parameters of some mixture models.Includes multi-response mixture models and also random coefficient mixture mo
丛书名称Lecture Notes in Statistics
图书封面Titlebook: Optimal Mixture Experiments;  B.K. Sinha,N.K. Mandal,P. Das Book 2014 Springer Nature India Private Limited 2014 Bayesian Analysis.Design o
描述.​The book dwells mainly on the optimality aspects of mixture designs. As mixture models are a special case of regression models, a general discussion on regression designs has been presented, which includes topics like continuous designs, de la Garza phenomenon, Loewner order domination, Equivalence theorems for different optimality criteria and standard optimality results for single variable polynomial regression and multivariate linear and quadratic regression models. This is followed by a review of the available literature on estimation of parameters in mixture models. Based on recent research findings, the volume also introduces optimal mixture designs for estimation of optimum mixing proportions in different mixture models, which include Scheffé’s quadratic model, Darroch-Waller model, log- contrast model, mixture-amount models, random coefficient models and multi-response model. Robust mixture designs and mixture designs in blocks have been also reviewed. Moreover, some applications of mixture designs in areas like agriculture, pharmaceutics and food and beverages have been presented. Familiarity with the basic concepts of design and analysis of experiments, along with the c
出版日期Book 2014
关键词Bayesian Analysis; Design of Experiments; Kiefer’s Equivalence Theorem; Linear Models; Loewner Order Dom
版次1
doihttps://doi.org/10.1007/978-81-322-1786-2
isbn_softcover978-81-322-1785-5
isbn_ebook978-81-322-1786-2Series ISSN 0930-0325 Series E-ISSN 2197-7186
issn_series 0930-0325
copyrightSpringer Nature India Private Limited 2014
The information of publication is updating

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发表于 2025-3-21 21:40:49 | 显示全部楼层
B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasfe and minimizes energy consumption for an underwater sensor network. The optimization algorithm uses the following state parameters to estimate network lifetime: (1) internode distance; (2) transmission frequency; (3) sampling frequency; and (4) number of descendants in the routing tree. Transmissi
发表于 2025-3-22 02:32:19 | 显示全部楼层
发表于 2025-3-22 05:45:23 | 显示全部楼层
B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasfe and minimizes energy consumption for an underwater sensor network. The optimization algorithm uses the following state parameters to estimate network lifetime: (1) internode distance; (2) transmission frequency; (3) sampling frequency; and (4) number of descendants in the routing tree. Transmissi
发表于 2025-3-22 10:20:39 | 显示全部楼层
发表于 2025-3-22 13:03:11 | 显示全部楼层
B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking net
发表于 2025-3-22 18:02:32 | 显示全部楼层
发表于 2025-3-22 23:38:51 | 显示全部楼层
B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking net
发表于 2025-3-23 03:06:13 | 显示全部楼层
B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking net
发表于 2025-3-23 08:17:19 | 显示全部楼层
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