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Stopping Rule (stopping + rule)
Selected AbstractsDesign of change detection algorithms based on the generalized likelihood ratio testENVIRONMETRICS, Issue 8 2001Giovanna Capizzi Abstract A design procedure for detecting additive changes in a state-space model is proposed. Since the mean of the observations after the change is unknown, detection algorithms based on the generalized likelihood ratio test, GLR, and on window-limited type GLR, are considered. As Lai (1995) pointed out, it is very difficult to find a satisfactory choice of both window size and threshold for these change detection algorithms. The basic idea of this article is to estimate, through the stochastic approximation of Robbins and Monro, the threshold value which satisfies a constraint on the mean between false alarms, for a specified window size. A convenient stopping rule, based on the first passage time of an F -statistic below a fixed boundary, is used to terminate the iterative approximation. Then, the window size which produces the most desirable out-of-control ARL, for a fixed value of the in-control ARL, can be selected. These change detection algorithms are applied to detect biases on the measurements of ozone, recorded from one monitoring site of Bologna (Italy). Comparisons of the ARL profiles reveal that the full-GLR scheme provides much more protection than the window-limited GLR schemes against small shifts in the process, but the modified window-limited GLR provides more protection against large shifts. Copyright © 2001 John Wiley & Sons, Ltd. [source] When has estimation reached a steady state?INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 1 2005The Bayesian sequential test Abstract This paper is concerned with distributions of time series, which (i) are influenced by initial conditions (ii) are stimulated by an exogenous signal or (iii) are obtained by recursive estimation of underlying parameters and thus undergo a transient period. In computer intensive applications, it is desirable to stop the processing when the transient period is practically over. This aspect is addressed here from a Bayesian perspective. Under an often met assumption that the model of a system's time series is recursively estimated anyway, the computational overhead of the constructed stopping rule is negligible. Algorithmic details are presented for important normal ARX models (auto-regression with exogenous variable) and models of discrete-valued, independent, identically distributed data. The latter case provides non-parametric Bayesian estimation of credibility interval with sequential stopping. Copyright © 2004 John Wiley & Sons, Ltd. [source] The PLS multivariate regression model: testing the significance of successive PLS componentsJOURNAL OF CHEMOMETRICS, Issue 6 2001Aziz Lazraq Abstract In this paper we write the PLS multivariate regression model in terms of a redundancy index and obtain some properties of the successive PLS components. We study their significance in the model and build tests of hypotheses to this effect. A stopping rule is given to obtain the right number of PLS components, and a numerical measure is defined to assess the overall quality of the PLS regression. Finally, an algorithm is given explicitly as it was coded in S-Plus and is applied in some chosen examples. Copyright © 2001 John Wiley & Sons, Ltd. [source] Sample Size Determination for Categorical ResponsesJOURNAL OF FORENSIC SCIENCES, Issue 1 2009Dimitris Mavridis Ph.D. Abstract:, Procedures are reviewed and recommendations made for the choice of the size of a sample to estimate the characteristics (sometimes known as parameters) of a population consisting of discrete items which may belong to one and only one of a number of categories with examples drawn from forensic science. Four sampling procedures are described for binary responses, where the number of possible categories is only two, e.g., licit or illicit pills. One is based on priors informed from historical data. The other three are sequential. The first of these is a sequential probability ratio test with a stopping rule derived by controlling the probabilities of type 1 and type 2 errors. The second is a sequential variation of a procedure based on the predictive distribution of the data yet to be inspected and the distribution of the data that have been inspected, with a stopping rule determined by a prespecified threshold on the probability of a wrong decision. The third is a two-sided sequential criterion which stops sampling when one of two competitive hypotheses has a probability of being accepted which is larger than another prespecified threshold. The fifth procedure extends the ideas developed for binary responses to multinomial responses where the number of possible categories (e.g., types of drug or types of glass) may be more than two. The procedure is sequential and recommends stopping when the joint probability interval or ellipsoid for the estimates of the proportions is less than a given threshold in size. For trinomial data this last procedure is illustrated with a ternary diagram with an ellipse formed around the sample proportions. There is a straightforward generalization of this approach to multinomial populations with more than three categories. A conclusion provides recommendations for sampling procedures in various contexts. [source] Reply: Might rapid virological response be used as a stopping rule in liver transplant recipients treated with pegylated interferon plus ribavirin?LIVER TRANSPLANTATION, Issue 9 2008Nizar N. Zein M.D. [source] A Lepskij,type Stopping-Rule for Newton-type Methods with Random NoisePROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2005Frank Bauer Regularized Newton methods are one of the most popular approaches for the solution of inverse problems in differential equations. Since these problems are usually ill-posed, an appropriate stopping rule is an essential ingredient of such methods. In this paper we suggest an a-posteriori stopping rule of Lepskij-type which is appropriate for data perturbed by random noise. The numerical results for this look promising. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Total System Reliability: Integrated Model for Growth and Test TerminationQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 4 2005John Donovan Abstract Reliability demonstration testing is not the most efficient method of assuring product reliability prior to shipment. It is costly, time consuming and has inherent technical and social limitations. The dilemma facing the reliability and quality engineer is whether to continue demonstration testing and risk shipping a product late or ship the product and risk warranty and field service returns. Either option can cause the company to lose significant market share and profit. This paper sets out to solve this dilemma by meeting both the time to market constraints and the product reliability goals. The weaknesses of existing reliability demonstration techniques are explored and a comprehensive methodology is introduced involving controlled development processes, stress testing, root cause determination and process change feedback mechanisms. All prototype products are manufactured on the final volume process line resulting in the early identification and correction of process-related problems. Testing commences on the first available prototypes with system stress/robust testing being employed to stimulate failures, determine their root cause and correct them. Reliability growth modelling assesses the ongoing improvements occurring in reliability during the development cycle, while a statistical stopping rule is used to determine the optimal product release time without risking product warranty. The approach is applicable to systems incorporating both hardware and software elements. The methodology has been validated on three development projects of telecommunication systems comprising hardware and software. In addition to enhancing team behaviour and performance, the development times have been reduced by 14% and the ramp-up time to full worldwide product shipments has been reduced by 50%. Copyright © 2005 John Wiley & Sons, Ltd. [source] Sequential design in quality control and validation of land cover databasesAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2009Elisabetta Carfagna Abstract We have faced the problem of evaluating the quality of land cover databases produced through photo-interpretation of remote-sensing data according to a legend of land cover types. First, we have considered the quality control, that is, the comparison of a land cover database with the result of the photo-interpretation made by a more expert photo-interpreter, on a sample of the polygons. Then we have analysed the problem of validation, that is, the check of the photo-interpretation through a ground survey. We have used the percentage of area correctly photo-interpreted as a quality measure. Since the kind of land cover type and the size of the polygons affect the probability of making mistakes in the photo-interpretation, we stratify the polygons according to two variables: the land cover type of the photo-interpretation and the size of the polygons. We have proposed an adaptive sequential procedure with permanent random numbers in which the sample size per stratum is dependent on the previously selected units but the sample selection is not, and the stopping rule is not based on the estimates of the quality parameter. We have proved that this quality control and validation procedure allows unbiased and efficient estimates of the quality parameters and allows reaching high precision of estimates with the smallest sample size. Copyright © 2009 John Wiley & Sons, Ltd. [source] Evaluation of fetuses in a study of intravenous immunoglobulin as preventive therapy for congenital heart block: Results of a multicenter, prospective, open-label clinical trial,ARTHRITIS & RHEUMATISM, Issue 4 2010Deborah M. Friedman Objective The recurrence rate of anti-SSA/Ro,associated congenital heart block (CHB) is 17%. Sustained reversal of third-degree block has never been achieved. Based on potential reduction of maternal autoantibody titers as well as fetal inflammatory responses, intravenous immunoglobulin (IVIG) was evaluated as preventive therapy for CHB. Methods A multicenter, prospective, open-label study based on Simon's 2-stage optimal design was initiated. Enrollment criteria included the presence of anti-SSA/Ro antibodies in the mother, birth of a previous child with CHB/neonatal lupus rash, current treatment with ,20 mg/day of prednisone, and <12 weeks pregnant. IVIG (400 mg/kg) was given every 3 weeks from week 12 to week 24 of gestation. The primary outcome was the development of second-degree or third-degree CHB. Results Twenty mothers completed the IVIG protocol before the predetermined stopping rule of 3 cases of advanced CHB in the study was reached. CHB was detected at 19, 20, and 25 weeks; none of the cases occurred following the finding of an abnormal PR interval on fetal Doppler monitoring. One of these mothers had 2 previous children with CHB. One child without CHB developed a transient rash consistent with neonatal lupus. Sixteen children had no manifestations of neonatal lupus at birth. No significant changes in maternal titers of antibody to SSA/Ro, SSB/La, or Ro 52 kd were detected over the course of therapy or at delivery. There were no safety issues. Conclusion This study establishes the safety of IVIG and the feasibility of recruiting pregnant women who have previously had a child with CHB. However, IVIG at low doses consistent with replacement does not prevent the recurrence of CHB or reduce maternal antibody titers. [source] How to use virological tools for optimal management of chronic hepatitis CLIVER INTERNATIONAL, Issue 2009Stéphane Chevaliez Abstract Chronic hepatitis C is a global health problem that may cause cirrhosis and progression to hepatocellular carcinoma. Currently available antiviral treatments are moderately effective. Several virological assays are available to help diagnose and manage patients infected with the hepatitis C virus (HCV). These include the anti-HCV antibody assays, measurement of HCV RNA viral load and HCV genotyping. HCV RNA can be assayed by two types of molecular biology-based techniques: target amplification as in polymerase chain reaction methods and signal amplification such as the branched DNA assay. Monitoring of viral kinetics during the early phases of antiviral treatment is crucial in making treatment decisions such as early stopping rules and also in optimizing the length of treatment. The HCV genotype can be determined by several methods. Whatever the method, pretreatment determination allows treatment length and ribavirin dose to be optimized and also offers prognostic information on treatment outcomes as certain genotypes respond more favourably to treatment. Thus, virological assays are indispensable in the diagnosis and management of individuals infected with the HCV. [source] Flexible and Robust Implementations of Multivariate Adaptive Regression Splines Within a Wastewater Treatment Stochastic Dynamic ProgramQUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2005Julia C. C. Tsai Abstract This paper presents an automatic and more robust implementation of multivariate adaptive regression splines (MARS) within the orthogonal array (OA)/MARS continuous-state stochastic dynamic programming (SDP) method. MARS is used to estimate the future value functions in each SDP level. The default stopping rule of MARS employs the maximum number of basis functions Mmax, specified by the user. To reduce the computational effort and improve the MARS fit for the wastewater treatment SDP model, two automatic stopping rules, which automatically determine an appropriate value for Mmax, and a robust version of MARS that prefers lower-order terms over higher-order terms are developed. Computational results demonstrate the success of these approaches. Copyright © 2005 John Wiley & Sons, Ltd. [source] | |||||||||||||||||||