The separation of signal and noise is a central issue in seismic data processing. The noise is both random and coherent in nature, the coherent part often masquerading as signal. In this tutorial, we present some approaches to signal isolation, in which stacking is a central concept. Our methodology is to transform the data to a domain where noise and signal are separable, a goal that we attain...

We consider some inference problems concerning the drift parameters vector of diffusion process. Namely, we consider the case where the parameters vector is suspected to satisfy certain restriction. Under such a design and imprecise prior information, we propose Stein-rule (or shrinkage) estimators which improves over the performance of the classical maximum likelihood estimator (MLE). By using...

The semiparametric accelerated failure time model relates the logarithm of the failure time linearly to the covariates while leaving the error distribution unspecified. The present paper describes simple and reliable inference procedures based on the least-squares principle for this model with right-censored data. The proposed estimator of the vectorvalued regression parameter is an iterative s...

To my family. My father and mother. Especially, to my beloved wife Ji-Hyun and my precious Catherine. iii ACKNOWLEDGEMENTS When I came to Georgia Tech, I used to imagine the moment when I graduate and thought that it would take forever to finish my graduate work. Since then, five years passed fast and I have finished my thesis. While I was writing this thesis, I could not help thinking that it ...

Applied researchers often confront two issues when using the fixed effect-two-stage least squares (FE-2SLS) estimator for panel data models. One is that it may lose its consistency due to too many instruments. The other gain of FE-2SLS not exceed loss endogeneity weak. In this paper, an L2Boosting regularization procedure models proposed tackle instruments issue. We then construct a Stein-like ...

We consider the problem of estimating an unknown, deterministic speech signal parameters based on quantum measurements corrupted by white Gaussian noise. We design and analyze blind minimax estimator (BME), which consist of a bounded parameter set. Using minimax estimator, the parameter set is itself estimated from quantum measurements. Thus, our approach does not require any prior knowledge of...

Algorithms to solve variational regularization of ill-posed inverse problems usually involve operators that depend on a collection of continuous parameters. When these operators enjoy some (local) regularity, these parameters can be selected using the socalled Stein Unbiased Risk Estimate (SURE). While this selection is usually performed by exhaustive search, we address in this work the problem...

BACKGROUND Optical coherence tomography (OCT) is a minimally invasive imaging technique, which utilizes the spatial and temporal coherence properties of optical waves backscattered from biological material. Recent advances in tunable lasers and infrared camera technologies have enabled an increase in the OCT imaging speed by a factor of more than 100, which is important for retinal imaging wher...

There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller’s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of ...