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 392 for “"Time Series Analysis"”.
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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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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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Time series analysis of macroeconometric constructs
… estimating persistence of economic shocks using time series models. First, it is shown that the log likelihood function for ARIMA models is not strictly quadratic with respect to the persistence estimate. This result explains why the persistence literature has attained conflicting results. In …
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Three essays in time series analysis
The first essay studies quantile impulse response functions (QIRFs) and their applications in macroeconomics and finance. We build a multi-equation autoregressive conditional quantile model and propose a new construction of the QIRF. We investigate dynamic QIRFs of the US economy in response to …
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Topics In Time Series Analysis And Forecasting
… contains new developments in various topics in time series analysis and forecasting. These topics include: model selec- tion, estimation, forecasting and diagnostic checking.;In the area of model selection, finite and large sample properties of the commonly used selection criteria, Akaike …
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Nonparametric Methods in Financial Time Series Analysis
The fundamental objective of the analysis of financial time series is to unveil the random mechanism, i.e. the probability law, underlying financial data. The effort to identify the truth that governs the observations involves proposing and estimating reasonable statistical models that well explain …
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Empirical Bayes methods in time series analysis
… the empirical Bayes estimates of various time series parameters: The autoregressive model, moving average model, mixed autoregressive-moving average, regression with time series errors, regression with unobservable variables, serial correlation, multiple time series and spectral density …
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Empirical Bayes procedures in time series analysis
Empirical Bayes analysis concerns the analysis of data which occur in similar recurring situations. The parameters involved in the recurring situations are generated independently from an unknown probability distribution G(θ). In many situations it is possible to use the estimates of all of the …
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Applications of time series analysis to geophysical data
… of three papers applying the techniques of time series analysis to geophysical data. Surface wave dispersion along the Walvis Ridge, South Atlantic Ocean, is obtained by bandpass filtering the recorded seismogram in the frequency domain. The group velocity is anomalously low in the period …
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The bootstrap approach to autoregressive time series analysis
Please read the abstract in the section 00front of this document Accompanied by 1 disc available at main counter with shelf number EM 519.5 DE KOSTER. Master copy at back of book
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Linear system identification technique by time series analysis
… dynamical systems using the finite difference time-domain (FDTD) method is inaccurate and problematic. This thesis investigates the use of time series analysis techniques for estimating parameters of a continuous-time (CT) model of linear dynamic systems. This application of time series …
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A Geometric Approach to Biomedical Time Series Analysis
<p>Biomedical time series are non-invasive windows through which we may observe human systems. Although a vast amount of information is hidden in the medical field's growing collection of long-term, high-resolution, and multi-modal biomedical time series, effective algorithms for extracting that …
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Machine learning and time-series analysis in healthcare
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01
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Applications of time series analysis to geophysical data
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Earth and Planetary Sciences, 1980.
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Time-series analysis of multivariate manufacturing data sets
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
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Time series analysis of ECG data and unreliable forecasting
… by observing individual Electrocardiograph (ECG) time series data. We usually use linear models because they are simple and easy to apply. But linear systems that are used to describe complex biological system such as ECG data are no longer satisfactory. For the ECG data , it is expected that a …
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Time Series Analysis of the A0 Supergiant HR 1040
<p>A time series analysis of spectroscopic and photometric observables of the A0Ia supergiant HR 1040 has been performed. The data, obtained from 1993 through 2007, include 152 spectroscopic observations from the Ritter Observatory and 269 Stromgren photometric observations from the Four College …
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Time series analysis for evaluation of antimicrobial stewardship interventions
… and in the hospital setting where, at any given time, approximately one third of all patients receive antibiotics. It is important to understand what antimicrobial stewardship interventions are effective in reducing inappropriate prescribing and influence resistance without worsening clinical …
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The demand for nonfarm housing: a time series analysis
… is about 0.35. The study is composed of static analysis and dynamic and analysis. On the contrary to relative abundance of static analyses, there have been very few dynamic studies. Furthermore, the distributed lag model which has been commonly adopted in the dynamic studies of housing demand …
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