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 19 of 19 for “"Autoregressive Moving Average (ARMA)"”.
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On stationary and nonstationary fatigue load modeling using autoregressive moving average (ARMA) models
… by a class of time series referred to as Autoregressive Moving Average (ARMA) models, while a Fourier series is used to account for the variation of the mean and variance. Due to the use of random phase angles in the Fourier series, an ensemble of mean and variance variations is obtained. …
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Dynamic Chemical Shift Imaging For Image-Guided Thermal Therapy
… spatiotemporal resolution. An algorithm based on autoregressive moving average (ARMA) modeling is developed and validated to help overcome limitations of Fourier-based analysis allowing highly accurate and precise PRF estimates. From the determined acquisition parameters and ARMA modeling, robust …
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Long Term Ground Based Precipitation Data Analysis: Spatial and Temporal Variability
… modeled and gauge data using: 1) Wavelets 2) Autoregressive-moving-average (ARMA) model / Empirical Mode Decomposition (EMD) 3) Vector Generalized Linear Model (VGLM). This dissertation aims to propose and evaluate a methodology for developing a model to measure ENSO events accurately. The …
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A modified approach for obtaining sieve bootstrap prediction intervals for time series
… but many early versions of such intervals for autoregressive moving average (ARMA) processes assume that the autoregressive and moving average orders, p, q respectively, are known, The sieve bootstrap, first introduced by Bühlmann in 1997, sidesteps this assumption for invertible time series by …
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Effect of manual digitizing error on the accuracy and precision of polygon area and line length
… Stream mode digitizing error was modeled using autoregressive moving average (ARMA) procedures, and point mode digitizing was stochastically simulated using an uniform random model. These models were developed based on quantification of digitizing error collected from several operators. The …
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Multiresolution fixation of a binocular vision system
… determines an initial window size using an Autoregressive-Moving Average (ARMA) modeling technique. Area-based feature matching is performed using normalized cross-covariance within a multiresolution image hierarchy. Gaussian low-pass filters of increasing spatial resolution are used to …
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Forecasting Wind Direction Across Very Short and Short Term Time Horizons for Wind Turbine Control
… wind direction forecasting: persistence, autoregressive moving average (ARMA), and ridge regression. The models were tested on several time horizons (Δ𝑇) that are relevant to turbine control and operation, ranging from 30 seconds to 2 hours. In this thesis, persistence demonstrated the …
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Essays on unit root testing in time series
… when the time series can be modeled using an autoregressive moving average (ARMA) process, such tests aim to determine if the autoregressive (AR) polynomial has one or more unit roots. The effect of economic shocks do not diminish with time when there is one or more unit roots in the AR …
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Adaptive feedforward control of broadband structural vibration
… loop is required to implement this algorithm. An autoregressive moving-average (ARMA) model was used for the system identification since it provides the most computationally-efficient means of representing the frequency response function (FRF) of a lightly-damped structure. In the first control …
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Linear system identification technique by time series analysis
… for system identification is based on the autoregressive moving-average (ARMA) model and its important characteristics. This thesis concentrates on the procedure of using time series analysis for identification of linear dynamical systems. The procedure consists of two steps. In the first …
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Analysis of Continuous Longitudinal Data with ARMA(1, 1) and Antedependence Correlation Structures
… structure generated by the first-order autoregressive-moving average (ARMA(1, 1)) stationary time-series model. ARMA(1, 1) correlation structure is characterized by two correlation parameters and this correlation structure reduces to the AR(1), MA(1) and CS structures in special cases. …
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Radar cross-section data encoding based on parametric spectral estimation techniques
… made. The most common parametric models are the autoregressive moving-average (ARMA), the moving-average (MA) and the autoregressive (AR) model. These models represent filters, which when excited by a white Gaussian noise sequence give some output sequence. If the parameters of the models and the …
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Modeling and Forecasting Ghana's Inflation Rate Under Threshold Models
… rate in Ghana using linear models such as Autoregressive Integrated Moving Average (ARIMA), Autoregressive Moving Average (ARMA) and Moving Average (MA). Empirical research however, has shown that financial data, such as inflation rate, does not follow linear patterns. This study seeks to …
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A Multilayer Framework for Quality of Context in Context-Aware Systems
… to traditional prediction methods such as moving average (MA), weighted moving average, exponential smoothing, doubled exponential smoothing, and autoregressive moving average (ARMA).
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Detection of network anomalies and novel attacks in the internet via statistical network traffic separation and normality prediction
… prediction technique, which is capable of removing both pulse and continuous anomalies. Furthermore we introduce and design dynamic thresholds, and based on them we define adaptive anomaly violation conditions, as a combined function of both the magnitude and duration of the traffic …
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Applications of Box-Jenkins methods of time series analysis to the reconstruction of drought from tree rings
… account for the effects of past years' climate. Autoregressive-moving-average (ARMA) modeling is used to screen out climatically insensitive tree-ring indices, and to estimate the lag in response to climate unmasked from the effects of autocorrelation in the tree-ring and climatic series. The …
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Sensing atmospheric water vapour using the global positioning system
… and detect linear trends. It is shown that an autoregressive moving average (ARMA) model is required to estimate realistic trend uncertainties, rather than the white-noise model implicit in standard least-squares analyses. Furthermore, significant trends in PWV were observed in South Africa …
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Modeling Autocorrelation and Sample Weights in Panel Data: A Monte Carlo Simulation Study
… or joint influence of autocorrelative processes (autoregressive-AR, moving average-MA, and autoregressive moving average-ARMA) and sample weights present in a longitudinal panel data set. Specifically, to what extent are the sample estimates influenced when autocorrelation (which is usually …
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Accounting for parameter uncertainty and temporal variability in coupled groundwater-surface water models using component and systems reliability analysis
The connections between streams and aquifers can be spatially variable and uncertain due to heterogeneity in geology and topography. During drought seasons, farming activities may induce critical peak pumping rates to supply irrigation water needs for crops. This may lead to increased concerns …