Robust Estimation and Hypothesis Testing



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 estimation in multiple linear regression model with non-Gaussian noise
Akkaya, Ayşen (2008-02-01)
The traditional least squares estimators used in multiple linear regression model are very sensitive to design anomalies. To rectify the situation we propose a reparametrization of the model. We derive modified maximum likelihood estimators and show that they are robust and considerably more efficient than the least squares estimators besides being insensitive to moderate design anomalies.
Robust quality metrics for assessing multimodal data
Konuk, Barış; Akar, Gözde; Department of Electrical and Electronics Engineering (2015)
In this thesis work; a novel, robust, objective, no-reference video quality assessment (VQA) metric, namely Spatio-Temporal Network aware Video Quality Metric (STNVQM), has been proposed for estimating perceived video quality under compression and transmission distortions. STN-VQM uses parameters reflecting the spatiotemporal characteristics of the video such as spatial complexity and motion. STN-VQM also utilizes parameters representing distortions due to compression and transmission such as bit rate and p...
Robust Tracking in Cellular Networks Using HMM Filters and Cell-ID Measurements
Bshara, Mussa; Orguner, Umut; Gustafsson, Fredrik; Van Biesen, Leo (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-01)
A localization algorithm based on cell identification (Cell-ID) information is proposed. Instead of building the localization decisions only on the serving base station, all the detected Cell-IDs (serving or nonserving) by the mobile station are utilized. The statistical modeling of user motion and the measurements are done via a hidden Markov model (HMM), and the localization decisions are made with maximum a posteriori estimation criterion using the posterior probabilities from an HMM filter. The results ...
Robust estimation of magnitude-frequency relationship parameters
Yücemen, Mehmet Semih; Akkaya, Ayşen (2012-01-01)
The precise estimation of the a and b parameters of Richter's magnitude-frequency relationship is of primary importance, since the evaluation of seismicity and assessment of seismic hazard depend on these two parameters. In the literature two popular methods of estimation are available for the estimation of these parameters, namely: least squares and maximum likelihood. However, in implementing these statistical methods, engineers very seldom check the validity of the underlying assumptions with respect to ...
Citation Formats
A. Akkaya, Robust Estimation and Hypothesis Testing. 2004.