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 101 for “"Auto-Regressive"”.
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Divide and recombine: Autoregressive models and STL+
… of Divide and Recombine estimates for Gaussian auto-regressive time series, Gaussian long range dependent series, and auto-regressive series with tails heavier than Gaussian.</p>
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The effects of educational experiences on personality trait development
… and personality traits. Finally, a series of auto-regressive and auto-regressive latent trajectory (ALT) models found evidence that educational experiences can lead to changes in personality traits and vice-versa. Overall, this study suggests that educational contexts are important for the …
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Optimal Linear Processing for Image and Video Coding
… inefficient at low bit rates. Using a Gaussian auto-regressive model, we propose the incorporation of rate-distortion optimized filters into the DPCM loop. It is shown that these filters trade off less important spectral components of the source for significant improvements in the …
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Time Series Forecasting Modeling for Demand of Emergency Department
… Average) 모델, 2) 단변량 - 계절형 ARIMA(Seasonal Auto- Regressive Integrated Moving Average) 모델, 3) 다변량 - 계절형 ARIMA(Seasonal Auto- Regressive Integrated Moving Average)모델을 구축하였다. 그리고, 각 모델의 적합도 평가를 위해 1) 잔차분석, 2) AIC(Akaike Information Criterion), BIC(Bayesian Information Criterion) 값을 비교•평가하였고, …
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Estimation of cardiovascular indices by analysis of the arterial blood pressure signal
… from the ABP signal. The algorithm utilizes an auto-regressive with exogenous input (ARX) model to describe the filter between ABF and ABP. Because ABF (the exogenous input to the peripheral circulation) is approximately zero during diastole, the diastolic ABP waveforms can be regarded as …
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Time series modelling of groundwater levels in a selected semi-arid catchment within Vhembe District Municipality, South Africa
… Vhembe District Municipality, South Africa. Auto Regressive Integrated Moving Average (ARIMA) model and Seasonal Auto Regressive Integrated Moving Average with eXogenous variables (SARIMAX) model were used to model the interaction between groundwater levels, temperature, wind speed, …
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Wind Speed Forecasting for Power Generation Using a Self-Assembling Closed-Loop Recurrent Neural Network
… recurrent neural network, NARX (Non-linear Auto-Regressive neural network with eXogenous inputs), on several univariate and multivariate time series, including weather measurements from the Bogdanci Wind Park in Macedonia. Artificial neural networks, such as NARX, require a good deal of …
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Growth constraints and external vulnerability in Argentina
… economic cycles depend on external shocks, auto-regressive vectors are used to characterize the short-run impact of these shocks on GDP, trade balance, and real wages. Results confirm that there is a bottleneck in the trade balance that blocks future growth possibilities, that GDP and wages …
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Budget deficit and economic growth in Namibia
… the period, 1990 to 2015. The study employed the Auto Regressive Distributed Lag (ARDL) Bounds Test and estimated the coefficients of the variables from the Error Correction Model in examining the relationship between budget deficit and economic growth. According to the cointegration test, the …
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An investigation of multi-dimensional evolutionary algorithms for virtual reality scenario development
… for this purpose – deterministic modeling, auto-regressive moving average modeling, genetic algorithm modeling, and hidden Markov modeling. Benefits, drawbacks, and trade-offs are evaluated with reference to their suitability for development in a VR environment. The methods developed in this …
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Statistical arbitrage in South African equity markets
… process) is estimated in discrete-time by an auto-regressive process with one lag (or AR(1) process). Trading signals are generated based on the level of the residual process. This strategy is then evaluated over historical data for the South African equity market from 2001 to 2013 through …
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Determinants of Economic Growth-The Case of Zimbabwe
… The study employed Unit Root Tests. The Auto Regressive Distributed Lag model was used to examine the mixed variable while the Ordinary Least Squares model and the Johansen test were used to examine all stationary and non-stationary variables respectively. In the case of co-integration, …
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Spatial modeling, covariate measurement error and design issues in environmental epidemiology
… variation in disease rates. The Conditional auto-regressive (CAR) structure within a hierarchical generalized linear model offers a robust, flexible, and popular class of models for the exploration and analysis of geographical variation across small areas. However, lack of modeling strategies …
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Parametric and nonparametric identification of shell and tube heat exchanger mathematical model
… could have parametric model structures such as auto regressive with external input, average auto regressive moves with external input, output error or box-jenkins. The study in this thesis aims to solve the general form through parametric and nonparametric models which has been proposed as …
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New hybrid automatic repeat request (HARQ) scheme for 4x4 MIMO system, based on the extended alamouti quasi-orthogonal space-time bloc coding (Q-STBC), in invariant and variant fading channel
A new Hybrid Automatic Repeat reQuest (HARQ) combining scheme for a 4x4 Multiple Input Multiple Output (MIMO) system in invariant and variant fading channel conditions is proposed and analized. Based on the Extended Alamouti Quasi-orthogonal Space-Time Block Coding (Q-STBC), the use of the …
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Monetary Policy And The Housing Market During The Last Decade
… January 2000 to July 2011, I estimate Vector Auto-regressive(VAR) models using data for each metropolitan statistical area (MSA) to analyze the interaction between local housing markets and monetary policy. Aggregate responses of housing variables to monetary policy are also estimated by …
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State-space modeling and optimal control of ship motions in a seastate
… for the ship motions is introduced. A discrete auto-regressive state-space model is developed using the state-of-the-art linear seakeeping simulation method SWAN. Novel features of this state-space model are its ability to capture all free-surface memory effects present in the seakeeping …
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Towards a Deeper Understanding of Neural Language Generation
… are (1) The general sampling behavior of an auto-regressive LM. In particular, we will take a closer look at the popular sampling algorithms. (2) Whether the LM is vulnerable to adversarial attacks, and how to make it more robust. (3) The LM’s ability to remember knowledge learned from data, …
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Spatiotemporal processing and time-reversal for underwater acoustic communications
… model. Multi-path fading was incorporated using auto regressive models. Simulations were conducted with various estimator delay scenarios for both the spatiotemporal focusing and simple time-reversal. Results demonstrate performance dependence on the non-dimensional product of estimation delay …
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Empirical Bayes procedures in time series analysis
… estimates of various time series parameters: the auto-regressive time series model, the time series regression model with auto-correlated errors and the spectral density function. In each case, empirical Bayes estimators are obtained using asymptotic or approximate distributions of the usual …
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