Browsing Statistics by Title
Now showing items 84-103 of 108
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Scalable Learning in Latent State Sequence Models
In this dissertation, we develop scalable learning methods for sequential data models with latent (hidden) states. State space models (SSMs) and recurrent neural networks (RNNs) are popular models for sequential data using ... -
Scalable Manifold Learning and Related Topics
The subject of manifold learning is vast and still largely unexplored. As a subset of unsupervised learning it has a fundamental challenge in adequately defining the problem but whose solution is to an increasingly important ... -
Scalable Methods for the Inference of Identity by Descent
Identity by descent (IBD) describes the shared inheritance of DNA and underlies genetic similarity between individuals. Estimated IBD graphs describing the IBD relationships among individuals have many uses in statistical ... -
Shape-Constrained Inference for Concave-Transformed Densities and their Modes
(2013-11-14)We consider inference about functions estimated via shape constraints based on concavity. We consider log-concave densities and other “concave-transformed” densities on the real line, where a concave-transformed class is ... -
Space-Time Contour Models for Sea Ice Forecasting
This dissertation develops statistical methods for modeling contours. Particular emphasis is placed on forecasting the sea ice edge contour, or the boundary around ocean areas that are ice-covered. Current sea ice forecasts ... -
Space-Time Smoothing Models for Surveillance and Complex Survey Data
Area and time-specific estimates of disease rates, cause-specific mortality rates and other key health indicators are of great interest for health care and policy purposes. Such estimates provide the information needed to ... -
Statistical analysis of low-frequency earthquake catalogs
Low-frequency earthquakes (LFEs) are small magnitude (less than 2) earthquakes, with reduced amplitudes at frequencies greater than 10 Hz relative to ordinary small earthquakes. They are usually grouped into families of ... -
Statistical Divergences for Learning and Inference: Limit Laws and Non-Asymptotic Bounds
Statistical divergences have been widely used in statistics and artificial intelligence to measure the dissimilarity between probability distributions. The applications range from generative modeling to statistical inference. ... -
Statistical Hurdle Models for Single Cell Gene Expression: Differential Expression and Graphical Modeling
This dissertation describes a set of statistical methods developed for analysis of single cell gene expression. A characteristic of single cell expression is bimodal expression, in which two clusters of expression are ... -
Statistical inference using Kronecker structured covariance
(2013-11-14)We present results for testing and estimation in the context of separable covariance models. We concentrate on two types of data: relational data and cross-classified data. Relational data is frequently represented by a ... -
Statistical Methods for Adaptive Immune Receptor Repertoire Analysis and Comparison
B and T cell receptors, also known as adaptive immune receptors, perform key roles in adaptive immunity. These proteins identify and deal with foreign invaders like viruses or bacteria, allowing for robust and long-lasting ... -
Statistical Methods for Clustering and High Dimensional Time Series Analysis
This dissertation mainly explores two statistical tasks, namely clustering and analysis of high-dimensional time series. Clustering, a very important unsupervised learning problem, studies the structure of unlabeled datasets. ... -
Statistical methods for genomic sequencing data
Genomic sequencing data has revolutionized our understanding of the genetic basis of biological processes. The cost of sequencing the first human genome was estimated to be greater than 50 million dollars. However, with ... -
Statistical Methods for Geospatial Modeling with Stratified Cluster Survey Data
The production of fine-scale, pixel level maps have become increasingly common in the current era of precision public health. This has led to the use of cluster level spatial models by major organizations such as WorldPop ... -
Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds
High-dimensional data sets often have lower-dimensional structure taking the form of a submanifold of a Euclidean space. It is challenging but necessary to develop statistical methods for these data sets that respect the ... -
Statistical Methods for the Analysis and Prediction of Hierarchical Time Series Data with Applications to Demography
This dissertation develops new methods for the analysis and prediction of hierarchical time series data with a focus on applications to demography. The first two projects aim to estimate and project the potential effect ... -
Statistical Modeling of Long Memory and Uncontrolled Effects in Neural Recordings
Scientific analyses of time series data are often formalized as statistical investigations targeting one or more aspects of a complex underlying dependence structure. In the multivariate time series setting, there are three ... -
Subnational Estimation of Period Child Mortality in a Low and Middle Income Countries Context
Child mortality is an important metric used in quantifying and monitoring the health of a population's children. Moreover, child mortality can be a key indicator of the overall health of a population, and is often used to ... -
Testing Independence in High Dimensions & Identifiability of Graphical Models
In this thesis two problems in multivariate statistics will be studied. In the first chaper, we treat the problem of testing independence between m continuous observations when m can be larger than the available sample ... -
Tests for Differences between Least Squares and Robust Regression Parameter Estimates and Related Topics
(2013-04-17)At the present time there is no well accepted test for comparing least squares and robust linear regression coefficient estimates. To fill this gap we propose and demonstrate the efficacy of two Wald-like statistical tests ...