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One-Stage Multiple Comparisons with the Control for Exponential Median Lifetimes under Heteroscedasticity

Shu-Fei Wu
2020 Mathematics  
When the additional sample for the second stage may not be available, one-stage multiple comparisons for exponential median lifetimes with the control under heteroscedasticity including one-sided and two-sided  ...  These intervals can be used to identify treatment populations that are better than the control or worse than the control in terms of median lifetimes in agriculture, stock market, pharmaceutical industries  ...  Acknowledgments: The author wish to thank an associate editor and referees for their careful reading and valuable suggestions so that the article is more readable and applicable.  ... 
doi:10.3390/math8091405 fatcat:xshpejzaprf6vjx7nfrptobaqy

Multiple Comparisons for Exponential Median Lifetimes with the Control Based on Doubly Censored Samples

Shu-Fei Wu
2020 Mathematics  
Under doubly censoring, the one-stage multiple comparison procedures with the control in terms of exponential median lifetimes are presented.  ...  The upper bounds, lower bounds and two-sided confidence intervals for the difference between each median lifetimes and the median lifetime of the control population are developed.  ...  Based on the doubly censored sample, Wu [8] proposed multiple comparisons with the average for exponential location parameters under heteroscedasticity.  ... 
doi:10.3390/math9010076 fatcat:6qlqwr7ohzdmxielt6vkpo3ghu

Multiple Comparison Procedures for Exponential Mean Lifetimes Compared with Several Controls

Shu-Fei Wu
2022 Mathematics  
Under heteroscedasticity, we propose one-stage multiple comparison procedures for several treatment groups compared with several control groups in terms of exponential mean lifetimes.  ...  Finally, one example of comparing the mean duration of remission using four drugs for treating leukemia is used for the aims of illustrations.  ...  Instead of comparing with the control, Wu [5] proposed one-stage multiple comparisons with the average for exponential location parameters.  ... 
doi:10.3390/math10040609 fatcat:ne3x6haryjd33cre3bitjgouwa

A note on the multiple comparisons of exponential location parameters with several controls under heteroscedasticity

Mahmood Kharrati-Kopaei, Ehsan Kharati Koopaei
2016 Hacettepe Journal of Mathematics and Statistics  
Several researchers have addressed the problem of constructing simultaneous condence intervals (SCIs) for comparing exponential location parameters with a control or controls under heteroscedasticity when  ...  In this paper, we present a set of SCIs for comparing exponential location parameters with a control, controls and the best control under heteroscedasticity when sample sizes are possibly unequal.  ...  The authors would like to acknowledge the Research Council of Shiraz University.  ... 
doi:10.15672/hjms.201612718540 fatcat:owadukjwencefitk5nh2kxnjo4

Page 7386 of Mathematical Reviews Vol. , Issue 94m [page]

1994 Mathematical Reviews  
A Bayesian approach to comparing treatments with a control. (English summary) Multiple comparisons, selection, and applications in biometry (Hamilton, ON, 1991), 267-292, Statist.  ...  Let 2; ,%2,---, 7, be k two-parameter exponential populations with m; having unknown location parameter (guaranteed lifetime) 4; and unknown (common) scale parameter o.  ... 

Page 2898 of Mathematical Reviews Vol. , Issue 95e [page]

1995 Mathematical Reviews  
STATISTICS 2898 95e:62022 62F07 Wen, Miin Jye (RC-TAIN-S; Tainan); Chen, Hubert J. (1-GA-S; Athens, GA) Single-stage multiple comparison procedures under heteroscedasticity. (English summary) Amer.  ...  Summary: “Given k (> 2) independent normal populations with unknown means and unknown (and possibly unequal) variances a single-stage sampling procedure for multiple comparisons with the largest normal  ... 

Page 4056 of Mathematical Reviews Vol. , Issue 94g [page]

1994 Mathematical Reviews  
The multivariate heteroscedastic method based on a two-stage sampling scheme has been formulated to allow inferences with controlled statistical characteristics in situations where the covari- ance matrices  ...  Ehsanes (3-CARL; Ottawa, ON); Shiraishi, Taka-aki (J-YOCU; Yokohama) Robust estimation for the parameters of multiple-design multivariate linear models under general restriction. (English summary) J.  ... 

Heteroscedastic Bayesian Optimisation for Stochastic Model Predictive Control [article]

Rel Guzman, Rafael Oliveira, Fabio Ramos
2020 arXiv   pre-print
To address these issues, we propose a Bayesian optimisation framework that accounts for heteroscedastic noise to tune hyper-parameters in control problems.  ...  Empirical results on benchmark continuous control tasks and a physical robot support the proposed framework's suitability relative to baselines, which do not take heteroscedasticity into account.  ...  BO Hyper-parameter Search Space and Function Scaling For better comparison, both BO variations were implemented using the same squared exponential kernel k(x, x ) = σ 2 n exp − (x−x ) 2 2 2 and UCB acquisition  ... 
arXiv:2010.00202v2 fatcat:3ecprpn3dzdtfnnr7groam7as4

A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise [article]

Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton, Jesse Berent
2020 arXiv   pre-print
We propose a simple probabilistic method for training deep classifiers under input-dependent (heteroscedastic) label noise.  ...  We illustrate that the softmax temperature controls a bias-variance trade-off for the approximation.  ...  The DeepLabv3+ method has three training stages; pretraining on JFT and MSCoco, followed by a training phase with output stride 16 (on augmented and/or coarsely labelled data) during which batch norm parameters  ... 
arXiv:2003.06778v3 fatcat:bbd6clrfvbfclp6tpank4t2jrq

Genotype by environment interaction for tick resistance of Hereford and Braford beef cattle using reaction norm models

Rodrigo R. Mota, Robert J. Tempelman, Paulo S. Lopes, Ignacio Aguilar, Fabyano F. Silva, Fernando F. Cardoso
2016 Genetics Selection Evolution  
The preferred model for the genetic evaluation of this population for tick counts in Brazilian climates was a one-step model that considered heteroscedastic residual variance.  ...  The objective of this study was to infer upon the existence of G*E interactions for tick resistance of cattle based on various models with different assumptions of genetic and residual variability.  ...  Acknowledgements The authors thank Delta G Connection for providing the data used in this research and CAPES and CNPq for granting the scholarships.  ... 
doi:10.1186/s12711-015-0178-5 pmid:26767704 pmcid:PMC5518165 fatcat:wjp3suvigzctpkxz7mapdlgke4

Detection of Multiple Change Points from Clustering Individual Observations

Joe H. Sullivan
2002 Journal of QualityTechnology  
In the preliminary analysis, also called Stage 1 analysis or retrospective analysis, of statistical process control, one may confront multiple shifts and/or outliers, especially with a large number of  ...  Suggestions are given for reducing masking and for diagnosing the number of shifts or outliers present. www.asq.org Hawkins (1976) briefly addresses the issue of estimating the number of change points  ...  Acknowledgments The author gratefully acknowledges the helpful suggestions of the Editor, Dr. Douglas M. Hawkins of the University of Minnesota, Dr. Zachary G.  ... 
doi:10.1080/00224065.2002.11980170 fatcat:ielhctxuyjg4zgq37yj5iifudm

Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy

Ahmed S. Elshall, Ming Ye, Guo-Yue Niu, Greg A. Barron-Gafford
2019 Geoscientific Model Development  
controls on carbon degradation; therefore, we have different levels of model complexity with respect to the number of model parameters.  ...  of the best model is generally justified by the cross-validation results for different data models; (ii) not accounting for heteroscedasticity and autocorrelation might not necessarily result in biased  ...  We thank the two anonymous reviewers for providing comments that helped to improve the paper. Review statement. This paper was edited by Christoph Müller and reviewed by two anonymous referees.  ... 
doi:10.5194/gmd-12-2009-2019 fatcat:wogeyf57mzeitpcetgq2bmjg7q

Spatial Linear Mixed Effects Modelling for OCT Images: SLME Model

Wenyue Zhu, Jae Yee Ku, Yalin Zheng, Paul C. Knox, Ruwanthi Kolamunnage-Dona, Gabriela Czanner
2020 Journal of Imaging  
and the eyes of healthy controls.  ...  study, involving 300 participants with diabetes and 50 age-matched controls.  ...  Acknowledgments: Wenyue Zhu would like to acknowledge the PhD funding from the Institute of Ageing and Chronic Disease and Institute of Transnational Medicine at University of Liverpool, and the Royal  ... 
doi:10.3390/jimaging6060044 pmid:34460590 fatcat:lmbhziobvzffvhrrtnrk4d5cum

A probabilistic methodology for quantifying, diagnosing and reducing model structural and predictive errors in short term water demand forecasting

Christopher J. Hutton, Zoran Kapelan
2015 Environmental Modelling & Software  
Accurate forecasts of water demand are required for real-time control of water supply systems under normal and abnormal conditions.  ...  An iteratively revised, parsimonious model using a formal Bayesian likelihood function that accounts for kurtosis and heteroscedasticity in the residuals led to sharper yet reliable predictive distributions  ...  Alongside the detection of abnormal conditions, the greater level of information on predictive uncertainty may also be useful for control optimisation under normal conditions.  ... 
doi:10.1016/j.envsoft.2014.12.021 fatcat:fx2wvsaw6bbg5h44ycxch37pmu

A cointegration approach for heteroscedastic data based on a time series decomposition: An application to structural health monitoring

Haichen Shi, Keith Worden, Elizabeth J. Cross
2019 Mechanical systems and signal processing  
Thus, in the current paper, an exponential smoothing method is presented to explore and deal with the complex seasonal patterns observed in SHM time series.  ...  The fact that the variance of heteroscedastic data is constantly changing has a significant negative impact on conventional damage detection algorithms, making it difficult to calculate accurate confidence  ...  The authors also thank Dr. Elena Barton from the National Physical Laboratory for providing us with the data of the NPL bridge project.  ... 
doi:10.1016/j.ymssp.2018.09.036 fatcat:trdt7zlagfb3fgzfil35larmya
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