• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.65-71
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• 2001

In this paper, optimal block designs for complete diallel crosses are proposed. These optimal block designs are constructed by using triangular partially balanced incomplete designs derived from symmetric balanced incomplete block designs. Also, it is shown that block designs for complete dialle crosses derived from complementary designs of triangular designs are optimal block designs.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.337-346
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• 2002

Complete diallel crosses using group divisible design with m=2 or n=2 and ${\lambda}_1$<${\lambda}_2$ as parameter designs become A-optimal, D-optimal designs. In case of ${\lambda}_2$=${\lambda}_1$+1, this blocked complete diallel crosses become generalized optimal designs.

• The Korean Journal of Applied Statistics
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• v.3 no.2
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• pp.55-77
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• 1990

In this paper we descuss some E-optimal block designs having unequal block sizes, and give a table of E-optimal designs with 2 different block sizes which can be constructed using the method described in Theorem 3. 2, Theorem 3. 4 and Theorem 3. 5 proved by Lee and Jacroux (1987). All of source designs used are Group Divisible designs which can be found in Clathworthy(1973) or Balanced Incomplete block designs in Raghavarar(1971).

• Journal of the Korean Statistical Society
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• v.15 no.2
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• pp.127-130
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• 1986

Constantine(1981) extended the results of Takeuchi(1961) by adding some new blocks to certain known E-optimal block design. But they are confined to equal blocksize designs. In this paper we agin generalize them to different blocksize case. By augmenting some known E-optimal block designs having blocks of equalsize with blocks of different sizes, additional E-optimal block designs are obtained.

• Journal of the Korean Statistical Society
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• v.16 no.2
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• pp.71-79
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• 1987

The linear and quadratic log contrast model with mixtures on the strictly positive simplex, $$ x_{q-1} = {(x_1, \cdots, x_q):\sum x_, = 1 and \delta \leq \frac{x_i}{x_j} \leq \frac{1}{\delta} for all i,j},$$ are considered. Using the invariance arguments, symmetric D-optimal designs are investigated. The class of symmetric D-optimal designs for the linear log contrasts model is given. Any D-optimal design for the quadratic log contrast model is shown to metric D-optimal designs for q=3 and 4 cases are given.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.889-902
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• 2017

Purpose: The orthogonality and trace optimal properties are desirable for constructing designs of experiments. This article focuses on the determination of the sizes of experiments for the balanced trace optimal resolution-V fractional factorial designs for 2-level factorial designs, which have near-orthogonal properties. Methods: In this paper, first we introduce the trace optimal $2^t$ fractional factorial designs for $4{\leq}t{\leq}7$, by exploiting the partially balanced array for various cases of experimental sizes. Moreover some orthogonality criteria are also suggested with which the degree of the orthogonality of the designs can be evaluated. And we appraise the orthogonal properties of the introduced designs from various aspects. Results: We evaluate the orthogonal properties for the various experimental sizes of the balanced trace optimal resolution-V fractional factorial designs of the 2-level factorials in which each factor has two levels. And the near-orthogonal 2-level balanced trace optimal resolution-V fractional factorial designs are suggested, which have adequate sizes of experiments. Conclusion: We can construct the trace optimal $2^t$ fractional factorial designs for $4{\leq}t{\leq}7$ by exploiting the results suggested in this paper, which have near-orthogonal property and appropriate experimental sizes. The suggested designs can be employed usefully especially when we intend to analyze both the main effects and two factor interactions of the 2-level factorial experiments.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.195-208
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• 2009

A conventional single design optimality criterion has been used to select an efficient experimental design. But, since an experimental design is constructed with respect to an optimality criterion pre specified by investigators, an experimental design obtained from one optimality criterion which is superior to other designs may perform poorly when the design is evaluated by another optimality criterion. In other words, none of these is entirely satisfactory and even there is no guarantee that a design which is constructed from using a certain design optimality criterion is also optimal to the other design optimality criteria. Thus, it is necessary to develop certain special types of experimental designs that satisfy multiple design optimality criteria simultaneously because these multi-optimal designs (MODs) reflect the needs of the experimenters more adequately. In this article, we present a heuristic approach to construct second-order response surface designs which are more flexible and potentially very useful than the designs generated from a single design optimality criterion in many real experimental situations when several competing design optimality criteria are of interest. In this paper, over cuboidal design region for $3\;{\leq}\;k\;{\leq}\;5$ variables, we construct multi-optimal designs (MODs) that might moderately satisfy two famous alphabetic design optimality criteria, G- and IV-optimality criteria using a GA which considers a certain amount of randomness. The minimum, average and maximum scaled prediction variances for the generated response surface designs are provided. Based on the average and maximum scaled prediction variances for k = 3, 4 and 5 design variables, the MODs from a genetic algorithm (GA) have better statistical property than does the theoretically optimal designs and the MODs are more flexible and useful than single-criterion optimal designs.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.677-683
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• 2001

In this paper, optimal block designs for complete diallel crosses are proposed. These optimal block designs for estimating general combining abilities are constructed by using balanced incomplete block designs and nested balanced incomplete block designs. Also, the efficiency of the optimal block design obtained through this method is reported in table.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.376-386
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• 1995

Designs for polynomial approximation to the unknown response function are considered. Optimality criteria are monotone functions of the mean squared error matrix of the least squares estimator. They correspond to the classical A-, D-, G- and Q-optimalities. Optimal first order designs are chosen from the invariant designs and then compared with optimal second order designs.

• International Journal of Reliability and Applications
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• v.2 no.2
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• pp.131-135
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• 2001

Two general methods of construction leading to several series of universally optimal block designs for complete diallel crosses are provided in this paper. A method of constructing variance balance designs is also given.