• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.563-574
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• 2004

Slope rotatability of response surface designs is a desirable property when we are interested in estimating slopes of response surfaces. In this paper, we derive a simplified measure of slope rotatability from new viewpoints for response surface designs that are frequently used in response surface methodology.

• Journal of the Korean Statistical Society
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• v.20 no.2
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• pp.147-155
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• 1991

This paper treats a robust design criterion which minimizes the effects of outliers and model inadequacy, and investigates robust designs for some response surface designs. In order to develop a robust design criterion and robust design, the integrated mean squared error of *(equation omitted) over a region is utilized, where *(equation omitted). is the estimated response by the minimum bias estimation proposed by carson, Manson and Hader (1969) . According to the number of aberrant observations and their positions, the proposed criterion and designs are studied. Also further development of the proposed criterion is treated when outliers can occur in any position of a design.

• Journal of the Korean Statistical Society
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• v.5 no.2
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• pp.101-107
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• 1976

One of the important properties of a 'good' response surface design is that the design should be insensitive to wild observations. In this note, a measure of sensitivity to wild observations is studied. It is shown that designs are made robust to wild observations by making $Tr[X'X)^{-1}M]$ small where M is a moment matrix over some region of interest. The proposed criterion is compared with that suggested by Box and Draper. Some about robust two-variable response surface designs are given.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.285-293
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• 2010

The traditional methods for evaluating response surface designs are alphabetic optimality criteria. These single-number criteria such as D-, A-, G- and V-optimality do not completely reflect the prediction variance characteristics of the design in question. Alternatives to single-numbers summaries include graphical displays of the prediction variance across the design regions. We can suggest the animated quantile plots as the animation of the quantile plots and use these animated quantile plots for comparing and evaluating response surface designs.

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.25-36
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• 2006

Icosahedron and dodecahedron designs are experimental designs which can be used for response surface analysis for the case when three independent variables are involved. When we are interested in estimating the slope of a response surface, slope rot at ability is a desirable property. In this paper, we derive conditions for icosahedron and dodecahedron designs to have slope rotatability, and actually obtain some slope-rotatable icosahedron and dodecahedron designs. We also apply Park and Kim (1992)'s measure of slope rotatability to icosahedron and dodecahedron designs, and observe resultant facts.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.557-578
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• 2007

In Response Surface Methodology (RSM), rotatability is a natural and highly desirable property. For second order general correlated regression model, the concept of robust rotatability was introduced by Das (1997). In this paper a new measure of robust rotatability for second order response surface designs with correlated errors is developed and illustrated with an example. A comparison is made between the newly developed measure with the previously suggested measure by Das (1999).

• Journal of Korean Society for Quality Management
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• v.27 no.1
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• pp.59-79
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• 1999

The fitting of a response surface model and the subsequent exploration of the response surface are usually based on the assumption that the experimental runs are carried out under homogeneous conditions. This, however, may be quite often difficult to achieve in many experiments. To control such an extraneous source of variation, the response surface design should be arranged in several blocks within which homogeneity of conditions can be maintained. In this case, when fitting a response surface model, the least squares estimates of the model's parameters and the prediction variance will generally depend on how the response surface design is blocked. That is, the choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of the prediction variance. In this paper, we propose a measure for evaluating the effect of blocking of response surface designs using cuboidal regions.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.741-757
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• 2000

In may experimental situations, whenever a block design is used, the block effect is usually considered to be fixed. There are, however, experimental situations in which it should be treated as random. The choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of he prediction variance even if the experimental runs re the same. Therefore, care should be exercised in the selection of blocks. In this paper, in the presence of a random block effect, we propose a graphical method or evaluating the effect of blocking in response surface designs using cuboidal regions. This graphical method can be used to investigate how the blocking has influence on the prediction variance throughout all experimental regions of interest when this region is cuboidal, and compare the block effects in the cases of the orthogonal and non-orthogonal block designs, respectively.

• Journal of Korean Society for Quality Management
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• v.29 no.1
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• pp.24-40
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• 2001

Response surface designs can be classified, according to the shape of the experimental region, into spherical designs and cuboidal designs. Among the central composite design(CCD)s and the Box-Behnken design(BBD)s that are popular in practice, when the number of factors is k, spherical designs are tile CCDs with the axial value being $\sqrt{\textit{k}}$ and the BBDs, and cuboidal designs are the CCDs with the axial value being 1. With the CCDs having $\sqrt{\textit{k}}$ as the axial value, the radius of the experimental region varies with number of factors, but these designs are the 5-level designs. With the BBDs that are 3-level designs, the radius of the experimental region does not vary with the number of factors. In this article, we propose tile 3-level spherical designs which are constructed so that tile radius of the experimental region varies with the number of factors.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.17-39
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• 1991

In many application of response surface methodology, good estimation of the derivatives of the response function may be as important or perhaps more important than estimation of mean response. Using a graphical method, we have studied the effect of outliers, missing observations, and design augmentation with respect to the slope estimation in the response surf ace designs.