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We describe an efficient method for solving an optimal control problem that arises in robust model-predictive control. The problem is to design the input sequence that minimizes the peak tracking erro...
Mass production of crop, produce, and food staff has resulted in great increase in the efficiency of food producing plants. This in turn has led to considerable decline in food prices. However, the ...
Most business processes are, by nature, multivariate and autocorrelated. Highdimensionality is rooted in processes where more than one variable is considered simultaneously to provide a more comprehen...
One of the major developments in recent years in the search for missing heritability of human phenotypes is the adoption of linear mixed-effects models (LMMs) to estimate heritability due to genetic v...
This article aims to consider a new univariate nonparametric cumulative sum (CUSUM) control chart for small shift of location based on both change-point model and Mann-Whitney statistic. Some comparis...
We prove that the linear step-up procedure $\vp^{LSU}$ considered by Benjamini and Hochberg (1995) controls the false discovery rate (FDR) in the case of dependent $p$-values whose dependency structur...
Baeet al. [6] consider the problem of optimal control of a finite dam usingPMλ,τpolicies, assuming that the input process is a compound Poisson process with a negative drift. Lam and Lou [8] treat th...
Baeet al. [6] consider the problem of optimal control of a finite dam usingPM兩,冄policies, assuming that the input process is a compound Poisson process with a negative drift. Lam and Lou [8] treat th...
We present an embedding of stochastic optimal control problems, of the so called path integral form, into reproducing kernel Hilbert spaces. Using consistent, sample based estimates of the embedding l...
Controller design for systems typically faces a trade-off between robustness and performance, and the reliability of linear controllers has caused many control practitioners to focus on the former. Ho...
Stability Selection was recently introduced by Meinshausen and B¨uhlmann (2010) as a very general technique designed to improve the performance of a variable selection algorithm. It is based on aggr...
In the classical version of the Bayesian quickest change detection problem proposed by Shiryaev, there is a sequence of observations whose distribution changes at a random time, and the goal is to m...
We construct a semiparametric estimator in case-control studies where the gene and the environment are assumed to be independent. A discrete or continuous parametric distribution of the genes is assum...
Woodall and Montgomery [35] in a discussion paper, state that multivariate process control is one of the most rapidly developing sections of statistical process control. Nowadays, in industry, there a...
When testing a large number of independent hypotheses, three different questions are of interest: are some hypotheses true alternatives? How many of them? Which of them? These questions give rise to...

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