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.
Results
Showing 1 to 20 of 32 for “"changepoint"”.
-
High-dimensional Online Changepoint Detection
The problem of changepoint detection and estimation has a long history, dating back to at least Page (1954, 1955). As modern technological advances, data sets of unprecedented size can be collected at high frequency. This provides statisticians with new challenges in this field. In this thesis we …
-
Efficient analysis of complex changepoint problems
… Detecting where these changes in structure, or changepoints, occur is required for effective modelling of the data. In this thesis we explore the common approaches used for detecting changepoints. We focus in particular on techniques which can be formulated in terms of minimising a cost over …
-
Changepoint detection for acoustic sensing signals
This thesis considers the application of changepoint detection methodology for the analysis of acoustic sensing signals. In the first part, we propose a detection procedure for changes in the second-order structure of a univariate time series. This utilises a penalised likelihood based on Whittle’s …
-
Direct Simulation Methods for Multiple Changepoint Problems.
The multiple changepoint model has been considered in a wide range of statistical modelling, as it increases the flexibility to simple statistical applications. The main purpose of the thesis enables the Bayesian inference from such models by using the idea of particle filters. Compared to the …
-
Parametric Resampling Methods for Retrospective Changepoint Analysis
Changepoint analysis is a useful tool in environmental statistics in that it provides a methodology for threshold detection and modeling processes subject to periodic changes in the underlying model due to anthropogenic effects or natural phenomena. Several applications of changepoint analysis are …
-
Flexible birth-death MCMC sampler for changepoint models
… der Bayessche Inferenz für eine Vielzahl von Changepoint-Modellen erlaubt. Die Struktur dieser Klasse von Modellen besteht aus zwei stochastischen Prozessen. Der erste Prozess wird entweder direkt beobachtet oder indirekt durch, möglicherweise verrauschte, Beobachtungen. Der zweite Prozess ist …
-
Computationally efficient Gaussian Process changepoint detection and regression
… the generalized likelihood ratio test to detect changepoints and learn multiple Gaussian Process models from streaming data. Furthermore, GP-NBC can quickly recognize and reuse previously seen models. The algorithm is shown to be theoretically sample efficient in terms of limiting mistaken …
-
Statistical estimation and changepoint detection methods in public health surveillance
This thesis focuses on assessing and improving statistical methods implemented in two areas of public health research. The first topic involves estimation of national influenza-associated mortality rates via mathematical modeling. The second topic involves the timely detection of infectious disease …
-
Changepoint detection and estimation for spatially indexed functional time series
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-05-01
-
Credit Risk Modeling and Analysis Using Copula Method and Changepoint Approach to Survival Data
… proposes a statistical procedure to identify changepoints in Cox model of survival data. The recent 2007-2009 financial crisis has been regarded as the worst financial crisis since the Great Depression by leading economists. The securitization sector took a lot of blame for the crisis because …
-
Finding a Better Confidence Interval for a Single Regression Changepoint Using Different Bootstrap Confidence Interval Procedures
… have been published in the area of regression changepoints but there is not much literature concerning confidence intervals for regression changepoints. The purpose of this paper is to find a better bootstrap confidence interval for a single regression changepoint. ("Better" confidence interval …
-
Scalable Autonomous Network Control using Minimally Informed Agents
… criticality studies and one study into network changepoint analysis were conducted. The first study was direct propagation of linearly increasing criticality over a generated network. When telecoms networks cannot route data packets to an asset because it is processing other packets, they are …
-
Real-time predictive modeling and robust avoidance of pedestrians with uncertain, changing intentions
… for robust collision avoidance. A novel changepoint detection and clustering algorithm (Changepoint-DPGP) is presented to enable quick detection of changes in pedestrian behavior and online learning of new behaviors not previously observed in prior training data. The resulting long-term …
-
Monte Carlo Methods in Practice and Efficiency Enhancements via Parallel Computation
… likelihood cannot be evaluated analytically, and changepoint models, which are often used to model the heterogeneity of sequential data, but tricky to infer upon due to the unknown number and locations of the changepoints. This thesis also focuses on the difficult task of performing parameter …
-
Spectral methods and computational trade-offs in high-dimensional statistical inference
… we consider the problem of high-dimensional changepoint estimation, where we estimate the time of change in the mean of a high-dimensional time series with piecewise constant mean structure. Motivated by real world applications, we assume that changes only occur in a sparse subset of all …
-
Functional data methods for climatological processes
… propose a computationally efficient and robust changepoint detector for functional data. We use this to test for, and estimate, changepoints in a long sequence of atmospheric interferometer profile measurements.
-
The performance analysis of power output in professional male road cyclists
… POpeak using a new time series analysis called changepoint. Changepoint estimated the four largest statistical changes in power output to find distinct segments. Seven professional male road cyclists (mean ± SD: age 29.5 ± 2.8 y, mass 69.7 ± 5.5 kg, height 182 ± 5 cm) participated in Study One …
-
A study of home advantage in football and other contributions to sports data analysis
… model. As an aside, weighted likelihood based changepoint methods were also explored as a method of considering the reduction in information about the threshold position carried by observations far from the threshold position. Finally, a brief but insightful analysis of changes of performance …
-
Efficient search methods for high dimensional time-series
… a novel approach to detect sets of most recent changepoints in panel data which aims to pool information across time-series, so that we preferentially infer a most recent change at the same time point in multiple series. Lastly, an approach to fit a sequence of piece-wise linear segments to a …
Page 1 of 2