Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 238 for “"statistical inference"”.
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Constrained Statistical Inference in Regression
… analysis constitutes a large portion of the statistical repertoire in applications. In case where such analysis is used for exploratory purposes with no previous knowledge of the structure one would not wish to impose any constraints on the problem. But in many applications we are interested …
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Statistical inference - theory and applications
Consists mainly of 33 articles and papers reprinted from journals
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Statistical inference on network data
… many real-world complex networks. However, both statistical inference and analytic study of such networks present great challenges. In Chapter 2, we propose new sequential importance sampling methods for sampling networks with a given degree sequence. These samples can be used to approximate …
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Statistical inference for dependent data
… of high-resolution climate projections through statistical downscaling, we consider the change point problem and the two sample problem for temporally dependent functional data. Specifically, in Chapter 1, we develop a self-normalization based test to test the structural stability of temporally …
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Statistical inference for complex networks
… In the past two decades, a large number of statistical methods have been proposed for modeling such relational data, identifying community structures, hypothesis testing, and model selection. The majority of these methods dealt with the case where only one network observation is available. …
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Topics In Differentially Private Statistical Inference
… the trade-off between differential privacy and statistical accuracy in parameter estimation problems. We understand the privacy-accuracy trade-off by finding the best achievable accuracy of any differentially private algorithm, also known as the "privacy-constrained minimax risk", in a series of …
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Statistical Inference for Diagnostic Classification Models
… models. The second part of the thesis focuses on statistical validation of the Q-matrix. The purpose of this study is to provide a statistical procedure to help decide whether to accept the Q-matrix provided by the experts. Statistically, this problem can be formulated as a pure significance …
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Statistical inference with unreliable binary observations
We describe a novel statistical inference approach to data conversion for mixed-signal interfaces. We propose a data conversion architecture in which a signal is observed by a set of sensors with uncertain parameters, such as highly scaled comparator circuits in an analog-to-digital converter. …
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Statistical inference for high-dimensional data
Statistical inference is a procedure of using collected observations to deduce properties of the underlying data generating process. In this thesis, we investigate three important problems in high-dimensional statistics and develop some new methods and theory, which show the limitation of some …
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Topics In Statistical Inference For Treatment Effects
… method, which examines the sensitivity of inferences to violations of IV validity. Our approach is based on extending the Anderson-Rubin test and is robust to weak IVs. The second paper presents a unified \proglang{R} software \pkg{ivmodel} for analyzing instrumental variables with one …
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Topics on statistical inference with model uncertainty
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Statistical inference in high-dimensional matrix models
… consider three such matrix models and develop statistical theory for them: Matrix completion, Principal Component Analysis (PCA) with Gaussian data and transition operators of Markov chains. \\ \\ We start with matrix completion and investigate the existence of adaptive confidence sets in the …
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Advanced Statistical Inference for Stochastic Quasi-Reaction Systems
Quasi-reaction systems are often modelled with stochastic differential equations in order to capture the inherent randomness of their dynamics. The traditional local linear approximation methods for the estimation of the reaction rates face significant challenges in certain conditions. When the …
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Towards More Automated Statistical Inference And Machine Learning
… keeps growing, the use of Machine Learning and statistical models has become more computationally demanding. Moreover, especially in industry applications, these models need to be trained quickly and efficiently, while also being updated frequently. With this increased complexity comes the …
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Statistical Inference and the Sum of Squares Method
Statistical inference on high-dimensional and noisy data is a central concern of modern computer science. Often, the main challenges are inherently computational: the problems are well understood from a purely statistical perspective, but key statistical primitives -- likelihood ratios, …
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Statistical inference in two non-standard regression problems
This thesis analyzes two regression models in which their respective least squares estimators have nonstandard asymptotics. It is divided in an introduction and two parts. The introduction motivates the study of nonstandard problems and presents an outline of the contents of the remaining chapters. …
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Statistical inference and computation in elliptic PDE models
… in describing real-world phenomena. In many statistical models, PDE are used to encode complex relationships between unknown quantities and the observed data. We investigate statistical and computational questions arising in such models, adopting an infinite-dimensional `nonparametric' …
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Polynomial methods in statistical inference: Theory and practice
… we apply the polynomial methods to several statistical questions with rich history and wide applications. The goal is to understand the fundamental limits of the problems in the large domain regime, and to design sample optimal and time efficient algorithms with provable guarantees. The …
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