Altay, Umut
Akkaya, Ayşen
Yucemen, M Semih


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).
Robust estimation and hypothesis testing in microarray analysis
Ülgen, Burçin Emre; Akkaya, Ayşen; Department of Statistics (2010)
Microarray technology allows the simultaneous measurement of thousands of gene expressions simultaneously. As a result of this, many statistical methods emerged for identifying differentially expressed genes. Kerr et al. (2001) proposed analysis of variance (ANOVA) procedure for the analysis of gene expression data. Their estimators are based on the assumption of normality, however the parameter estimates and residuals from this analysis are notably heavier-tailed than normal as they commented. Since non-no...
Robust parameter design of products and processes with an ordinal categorical response using random forests
Gülbudak Dil, Seçil; Köksal, Gülser; Department of Industrial Engineering (2018)
In industrial organizations, manufacturers aim to achieve target product performance with minimum variation. For that reason, finding optimal settings of product and process design parameters that make it possible to consistently achieve target product performance is an important design problem. In this study, we propose an alternative method to solve this problem for the case of an ordinal categorical product/process response. The method utilizes Random Forest (RF) for modelling mean and variance of the re...
Robust Linear Mixed Models with Kotz type Distributions
Gökalp Yavuz, Fulya (null; 2014-05-14)
Robust conditional value–at–risk under parallelpipe uncertainty: an application to portfolio optimization
Kara, Güray; Weber, Gerhard Wilhelm; Department of Financial Mathematics (2016)
In markets with high uncertainties, the trade–off between maximizing expected return and minimizing the risk is one of the main challenges in modeling and decision making. Since investors mostly shape their invested amounts towards certain assets and their risk version level according to their returns; scientists and practitioners has done studies on this subject since the beginning of the stock markets’ establishment. Developments and inventions in the mathematical optimization provide a wide range of solu...
Citation Formats
U. Altay, A. Akkaya, and M. S. Yucemen, “ROBUST AND BAYESIAN PARAMETER ESTIMATION IN TIME DEPENDENT SEISMIC HAZARD ANALYSIS,” 2017, Accessed: 00, 2021. [Online]. Available: