Univariate and multivariate linear profiles using max type extended exponentially weighted moving average schemes

Many studies have shown that industrial as well as non-industrial business organizations present a growing need of robust and more efficient multivariate monitoring schemes in order to be able to monitor several quality characteristics simultaneous. To monitor two or more parameters simultaneously, several monitoring schemes are used concurrently in most of the cases instead of using a single scheme. Thus, in this paper, the exponentially weighted moving average (EWMA), double EWMA (DEWMA) and the recent triple EWMA (TEWMA) procedures are used to develop new single univariate and multivariate Max-type monitoring schemes for linear profiles under the assumptions of fixed and random linear models to monitor the regression parameters and variance error simultaneously. It is observed that the newly proposed schemes are better alternatives of the classical univariate and multivariate EWMA, DEWMA and TEWMA schemes for linear profiles in terms of the average run-length (ARL) and expected ARL profiles. Numerical examples are presented using simulated and real-life data.https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639Statistic

Search designs for searching for one among the two-and three-factor interaction effects in the general symmetric and asymmetric factorials

Main-effect, two-and three-factor interaction,

A new look at discrete discrepancy

The objective of this paper is to study the issue of discrete discrepancy [Hickernell, F.J., Liu, M.Q., 2002. Uniform designs limit aliasing. Biometrika 89, 893-904; Fang, K.T., Lin, D.K.J., Liu, M.Q., 2003. Optimal mixed-level supersaturated design. Metrika 58, 279-291; Qin, H., Fang, K.T., 2004. Discrete discrepancy in factorial designs. Metrika 60, 59-72], which has wide application to the field of fractional factorial designs. Here we present an improved lower bound to discrete discrepancy.

A multivariate triple exponentially weighted moving average control chart

Statistical process monitoring (SPM) is mostly populated with univariate control charts used to monitor a single variable (or quality characteristic). Nowadays, industries and online environments are filled with processes in which two or more quality characteristics are related. In such situations, univariate control charts are replaced with multivariate control charts for the sake of monitoring several characteristics simultaneously. This paper develops a new multivariate triple exponentially weighted moving average (MTEWMA) chart to serve this purpose. Moreover, the design of the multivariate simple and double exponentially weighted moving average (denoted as MEWMA and MDEWMA) charts are revisited using extensive simulations. It is observed that the MTEWMA chart has very interesting time-varying properties as compared to the asymptotic properties. The newly proposed MTEWMA chart is superior over the MEWMA and MDEWMA charts in many situations of the asymptotic control limits. An illustrative example is provided to demonstrate the sensitivity of the proposed charts.http://wileyonlinelibrary.com/journal/qre2022-12-08hj2022Statistic

Supersaturated designs with high searching probability

Abstract A supersaturated design is essentially a fractional factorial design whose number of experimental variables is greater than or equal to its number of experimental runs. Under the effect sparsity assumption, a supersaturated design can be very cost-effective. In this paper, our prime objective is to compare the existing two-level supersaturated designs for the noisy case through the probability of correct searching-a powerful criterion proposed b

Homogeneously Weighted Moving Average Control Charts: Overview, Controversies, and New Directions

The homogeneously weighted moving average (HWMA) chart is a recent control chart that has attracted the attention of many researchers in statistical process control (SPC). The HWMA statistic assigns a higher weight to the most recent sample, and the rest is divided equally between the previous samples. This weight structure makes the HWMA chart more sensitive to small shifts in the process parameters when running in zero-state mode. Many scholars have reported its superiority over the existing charts when the process runs in zero-state mode. However, several authors have criticized the HWMA chart by pointing out its poor performance in steady-state mode due to its weighting structure, which does not reportedly comply with the SPC standards. This paper reviews and discusses all research works on HWMA-related charts (i.e., 55 publications) and provides future research ideas and new directions

Optimality of orthogonally blocked diallels with specific combining abilities

Optimality of orthogonally blocked complete diallel crosses for estimating general combining abilities is investigated when the model also includes specific combining abilities. It is proved that these designs remain optimal even in the presence of specific combining abilities. Three new series of orthogonally blocked designs are also reported.Balance Diallel cross Optimal Orthogonal Triangular design

Not Available

Not AvailableThis article deals with the problem of obtaining efficient designs for 2-color microarray experiments where same set of genes are spotted on each array. In the literature, optimality aspects of designs for microarray experiments have been investigated under a restricted model invloving array and variety effects. The dye effects have been ignored from the model. If dye effects are also included in the model, then the structure of the design becomes that of a row-column design where arrays represent columns, dyes represent rows and varieties represent treatments. Further, the array effects in microarray experiments may be taken as random (see e.g. Kerr and Churchill (2001a), Lee(2004)). For obtaining efficient row-column designs under fixed/mixed effects model, exchange and interchange algorithms of Eccleston and Jones(1980) and Rathore et al. (2006) have been modified. The algorithm has been translated into a computer program using Microsoft Visual C++. The algorithm is general in nature and can be used for generating efficient row-column designs for any 2 <= k < v, where v is the number of treatments (varieties) and k is number of rows(dyes). Here, the algorithm has been exploited for computer aided search of efficient row-column designs for making all possible pairwaise treatment comparisons for k = 2 (2-color microarray experiments) in the parametric range 3 <= v <= 10, v <= b <= v(v-1)/2; 11<=v <= 25, b = v and (v, b) = (11,13), (12,14), (13,14) and (13,15), where b is the number of arrays (columns). Efficient row-column designs obtained with higher efficiencies than the best available designs and even designs. The robustness aspect of efficient row-column designs obtained under fixed effects model and best available designs were investigated under a mixed effects model. Strength of the algorithm for obtaining row-column designs for 3-color microarray experiments has been demonstrated with the help of examples.Not Availabl