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 113 for “"autoregressive model"”.
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A multivariate autoregressive model for limited area weather forecasting
… research and operational weather prediction models. We give a complete description of the implementation of the multivariate autoregressive research model. This includes a FORTRAN program and three order selection routines. We conclude with a discussion on possible extensions of our results …
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A MULTI-COUNTRY LINK VECTOR AUTOREGRESSIVE MODEL THEORY AND EVIDENCE
… is an alternative to structural econometric model building, specifically in forecasting. The challenge of the VAR technique has been, however, limited to models of national and regional economies.</p><p>This dissertation extends the scope of the VAR technique with the construction of a …
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Three Essays on the Spatial Autoregressive Model in Spatial Econometrics
The spatial autoregressive model (SAR) is a standard tool to analyze spatial data. It is of great interest in econometrics because it has a game structure and, therefore, can be interpreted as a reaction function: the outcome or behavior of observations at one location is directly affected by those …
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Inferring Biological Networks from Time-Course Observations Using a Non-linear Vector Autoregressive Model
… an in silico E. coli network, we show that by modeling higher order interactions, the proposed method improves on earlier work that only considered linear interactions. We further show empirically that our proposed model selection criteria provides a good balance between sensitivity and …
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The Simultaneous Spatial Autoregressive Model and Its Application in the Housing and Pharmaceutical Markets
… research focuses on the extension of the spatial autoregressive (SAR) model into a system of simultaneous equations. The resulting new model is useful in studying problems involving multiple networks where individuals are not only linked to members of the same network but also interact with …
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Time-Varying Autoregressive Model Based Signal Processing with Applications to Interference Rejection in Spread Spectrum Communications
… non-stationary signals based on time-varying autoregressive (TVAR) modeling, and to apply such methods to frequency-modulated (FM) interference rejection in direct-sequence spread spectrum (DSSS) communications. For fast varying non-stationary signal processing, such as the task to reject an …
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An empirical comparison of autoregressive and rational models of price expectations
… to measure the relative abilities of alternative models in capturing the unobservable process by which economic individuals may form expectations of future inflation. Three empirical representations of the inflation expectations process are tested: an autoregressive model which uses only past …
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Modeling Daily Power Demand in Southern Kentucky: A Single Household Approach
… and compare it to existing aggregate demand models discussed in literature. Of these aggregate demand models, a quadratic autoregressive model was selected to be used as a basis for comparison with the LOESS forecasts. It was our goal to automate the forecasting process by using the goodness …
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Simulation of an algorithm for the active control of combustion noise
… in this thesis. The simulation includes (1) an autoregressive model of real combustion noise, (2) a feedback loop based on the "observer" method, (3) a model of the transfer function between the acoustic driver and the sensor through the flame, and (4) a method to take into account the …
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Polling and political behavior : explaining inaccuracy in Italian polling
… effect using OLS and multivariate regression models, where the days and polling houses and the methodologies employed by pollsters are the explanatory variables respectively. To estimate the extent of voters sentiment change in Italian voters, we apply the autoregressive model. The evidence …
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Robust speech filtering in impulsive noise environments
… to detect segments of speech with impulses. The autoregressive model employed to smooth out the speech signal is identified by means of a robust nonlinear estimator known as the Schweppe-type Huber GM-estimator. Simulation results are presented that demonstrate the effectiveness of the filter. …
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Modeling Conditional Heteroskedasticity in Time Series and Spatial Analysis
… derive a simple specification test for spatial autoregressive model using the information matrix (IM) test principle. As a byproduct of my test development, I obtain a general model that has similar features like autoregressive conditional heteroskedasticity (ARCH) in time series context. My …
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Study of the Kalman filter for arrhythmia detection with intracardiac electrograms
… use of Kalman filter applied on cyclostationary autoregressive model. This new algorithm was developed with a training set of 24 arrhythmia passages and tested on a different data set of 29 arrhythmia passages. The algorithm provides 100% detection of VF on the test set. 77.8% of VTs were …
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Nonlinear network vector autoregression
As we all know, the time series model is one of the most important aspects of modern econometric analysis. The autoregressive model is the theoretical basis of time series. The classic autoregressive model has two features that can be improved, linear, and one-dimensional. Economic theory shows …
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Otimização implícita estocástica para operação de reservatórios
… as well as the dependence (first order linear autoregressive model) in the stochastic component. Then a probability distribution was adjusted to the independent stochastic component. The structural model was used to generate several series of monthly streamflows in which critical periods were …
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Modelagem estocástica para a precipitação diária
The stochastic daily precipitation modeling is the main objective of this dissertation. The occurrence of the process was modeled by a two-state (dry or rainy day) Markov chain and by the “wet-dry spell” approach. This second approach was considered appropriate, while the Markov chains could not …
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A system for the acquisition and digital analysis of lower limb flow waveforms
… Power Spectral Density is calculated using an autoregressive model from which the mean velocity waveform is calculated. This waveform is used to calculate the damping factor, vessel compliance and runoff resistance of a simple electrical model of the lower limb arterial circulation using a …
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Monte Carlo Examination of Static and Dynamic Student t Regression Models
… to Static and Dynamic Student t Regression Models. The Static Student t Regression Model is derived and transformed to an operational form. The operational form is then examined in a series of Monte Carlo experiments. The model is judged based on its usefulness for estimation and testing and …
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STATISTICAL MODELING FOR COMPLEX FUNCTIONAL AND NETWORK TIME SERIES DATA
… and prediction. We developed three statistical modeling to investigate the dynamic behaviors of high dimensional data with either seasonality entangling with serial dependence or cross dependence among multiple time series data or network connection. In particular, we developed a Warping …
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