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 2878 for “"Time series"”.
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Unsupervised Time Series Anomaly Detection Using Time Series Foundational Models
The rapid generation of time series data across a wide array of domains—such as finance, healthcare, and industrial systems—has made anomaly detection a critical task for identifying irregular patterns that could signal significant events like fraud, system failures, or health crises. Traditional …
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On Explosive Time Series
The first chapter of this thesis, discusses the characteristics of an asset bubble episode outlining the reasons these episodes have attracted so much interest nowadays and provides an overview of historical bubble episodes motivating the testing procedures proposed in Chapters 2-4. The second …
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Geometric Multimedia Time Series
… thesis provides a new take on problems in multimedia times series analysis by using a shape-based perspective to quantify patterns in time, which is complementary to more traditional analysis-based time series techniques. Inspired by the dynamical systems community, we turn time series into …
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Algorithms in time series
… linear models such as ARMA models in analysing time series data has been extensively studied and in recent years there has been an increasing emphasis on the development of fast regression—based algorithms for the problem of model identification. In this thesis we investigate the statistical …
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Algorithms in time series
… linear models such as ARMA models in analysing time series data has been extensively studied and in recent years there has been an increasing emphasis on the development of fast regression—based algorithms for the problem of model identification. In this thesis we investigate the statistical …
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Time Series Analysis of Bitcoin
… dynamics of the daily Bitcoin/USD exchange rate series display episodes of local trends, which are modelled and interpreted as speculative bubbles. The structure of the Bitcoin market is described to give context for the presence of multiple bubbles in the exchange rate. The bubbles may result …
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Anomaly detection of time series.
… deals with the problem of anomaly detection for time series data. Some of the important applications of time series anomaly detection are healthcare, eco-system disturbances, intrusion detection and aircraft system health management. Although there has been extensive work on anomaly detection …
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Retail Price Time Series Imputation
A regular, discrete time series is an ordered sequence of coarse-grained observations taken at fixed time intervals. Here we consider regular, discrete, retail price time series datasets acquired through crowdsourcing. Crowdsourcing is a means of data collection whereby independent individuals push …
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Generalized structural time series model
A new class of univariate time series models is developed, the Generalized Structural (GEST) time series model. The GEST model extends Gaussian structural time series models by allowing the distribution of the dependent variable to come from any parametric distribution, including highly skew and=or …
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Topics in Nonstationary Time Series
… data. Missing prices during non-trading time periods are imputed iteratively during the estimation of model parameters. The study shows that the market trading on the announcement day is different from the market trading on a reference day for both the Eurodollar and T-Note futures market.
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Essays on Time Series Modeling
… hypothesis for Brazil. In this chapter we use time series techniques to model the long-run dynamics of the Brazilian inflationary process. Our results reveal that, although there is some inertia in the Brazilian inflation, the degree of inertia is rather small. Another important policy issue …
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Manifold Learning From Time Series
We apply our manifold learning algorithm to synthetic data and real world applications. The experiment on synthetic data clearly demonstrates that by taking temporal dependency among global coordinates into consideration our proposed algorithm achieves superior learning results than other manifold …
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Diagnostic Checking, Time Series and Regression
… checking ARMA, VAR, FGN, GARCH, and TAR time series models as well as for checking randomness of series and goodness-of- fit VAR models with stable Paretian errors. The asymptotic distribution of the test statistic is derived as well as a chi-square approximation. However, the Monte-Carlo …
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Time-series stochastic process and forecasting
Photocopy of typescript.
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Modeling time series of count data
The focus of this thesis is on modeling time series of count data. We consider an extension of linear Gaussian state space models - parameter driven models in which th e mean function of a time series of observed counts {Yt} is specified bv a linear predictor modified by a 'latent process’. As in …
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Time-series analysis using orthogonal polynomials
… of models and simulators of non-linear time-series. Researchers in the field of both science and statistics have come up with innovative methods that are useful in extracting information from systems that exhibit non-linear dynamics. Time-series, as we all know, is the sequence x1, x2, …
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Interpretable Deep Learning for Time Series
Time series data emerge in applications across many critical domains, including neuroscience, medicine, finance, economics, and meteorology. However, practitioners in such fields are hesitant to use Deep Neural Networks (DNNs) that can be difficult to interpret. For example, in clinical research, …
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