Robust control charts

Çetinyürek, Aysun
Control charts are one of the most commonly used tools in statistical process control. A prominent feature of the statistical process control is the Shewhart control chart that depends on the assumption of normality. However, violations of underlying normality assumption are common in practice. For this reason, control charts for symmetric distributions for both long- and short-tailed distributions are constructed by using least squares estimators and the robust estimators -modified maximum likelihood, trim, MAD and wave. In order to evaluate the performance of the charts under the assumed distribution and investigate robustness properties, the probability of plotting outside the control limits is calculated via Monte Carlo simulation technique.


A computational approach to nonparametric regression: bootstrapping cmars method
Yazıcı, Ceyda; Batmaz, İnci; Department of Statistics (2011)
Bootstrapping is a resampling technique which treats the original data set as a population and draws samples from it with replacement. This technique is widely used, especially, in mathematically intractable problems. In this study, it is used to obtain the empirical distributions of the parameters to determine whether they are statistically significant or not in a special case of nonparametric regression, Conic Multivariate Adaptive Regression Splines (CMARS). Here, the CMARS method, which uses conic quadr...
Multiple frame sampling theory and applications
Dalçık, Aylin; Ayhan, Hüseyin Öztaş; Department of Statistics (2010)
One of the most important practical problems in conducting sample surveys is the list that can be used for selecting the sample is generally incomplete or out of date. Therefore, sample surveys can produce seriously biased estimates of the population parameters. On the other hand updating a list is a difficult and very expensive operation. Multiple-frame sampling refers to surveys where two or more frames are used and independent samples are taken respectively from each of the frames. It is assumed that the...
Robust estimation and hypothesis testing under short-tailedness and inliers
Akkaya, Ayşen (Springer Science and Business Media LLC, 2005-06-01)
Estimation and hypothesis testing based on normal samples censored in the middle are developed and shown to be remarkably efficient and robust to symmetric short-tailed distributions and to inliers in a sample. This negates the perception that sample mean and variance are the best robust estimators in such situations (Tiku, 1980; Dunnett, 1982).
Analysis of Covariance with Non-normal Errors
ŞENOĞLU, BİRDAL; Avcioglu, Mubeccel Didem (Wiley, 2009-12-01)
P>Analysis of covariance techniques have been developed primarily for normally distributed errors. We give solutions when the errors have non-normal distributions. We show that our solutions are efficient and robust. We provide a real-life example.
Effect of estimation in goodness-of-fit tests
Eren, Emrah; Sürücü, Barış; Department of Statistics (2009)
In statistical analysis, distributional assumptions are needed to apply parametric procedures. Assumptions about underlying distribution should be true for accurate statistical inferences. Goodness-of-fit tests are used for checking the validity of the distributional assumptions. To apply some of the goodness-of-fit tests, the unknown population parameters are estimated. The null distributions of test statistics become complicated or depend on the unknown parameters if population parameters are replaced by ...
Citation Formats
A. Çetinyürek, “Robust control charts,” M.S. - Master of Science, Middle East Technical University, 2006.