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搜索结果: 1-10 共查到理论统计学 E-optimal Designs相关记录10条 . 查询时间(0.056 秒)
The interference model has been widely used and studied in block experiments where the treatment for a particular plot has effects on its neighbor plots. In this paper, we study optimal circular desig...
The interference model has been widely used and studied in block experiments where the treatment for a particular plot has effects on its neighbor plots. In this paper, we study optimal circular desig...
The paper extends the result of Harman and Pronzato [Stat. & Prob. Lett., 77:90--94, 2007], which corresponds to $p=0$, to all strictly concave criteria in Kiefer's $\phi_p$-class. Let $\xi$ be any de...
In statistics, experimental designs are methods for making efficient experiments. E-optimal designs are the multisets of experimental conditions which minimize the maximum axis of the confidence ellip...
The celebrated de la Garza phenomenon states that for a polyno- mial regression model of degree p−1 any optimal design can be based on at most p design points. In a remarkable paper, Yang [Ann...
We consider the problem of obtaining locally D-optimal designs for factorial exper- iments with qualitative factors at two levels each with binary response. For the 22 factorial experiment with main...
We study a class of multiplicative algorithms introduced by Silvey et al. (1978) for com- puting D-optimal designs. Strict monotonicity is established for a variant considered by Titterington (1978)...
We discuss the optimal design problem in regression models with long-range dependence error structure. Asymptotic optimal designs are derived and it is demonstrated that these designs depend only in...
We propose a new approach for identifying the support points of a locally optimal design when the model is a nonlinear model. In contrast to the commonly used geometric approach, we use an approach...
We construct optimal designs for estimating fetal malformation rate, prenatal death rate and an overall toxicity index in a toxicology study under a broad range of model assumptions. We use Weibull ...

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