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 55 for “"Time series model"”.
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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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A Strategy for Monetary Policy Using a Multiple Time-Series Model
… information sets and emphasizing the use of time series models in the process. While the combination of forecasts is not new, the combination of time series models and the more traditional structural econometric models has not been thoroughly evaluated.
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Detection of Event Related Potentials by Time Series Model Fitting Techniques
Made available in DSpace on 2014-12-13T18:21:37Z (GMT). No. of bitstreams: 1 7616140.pdf: 5134377 bytes, checksum: 10e41c14dc3d226c8f1be9d70fba350a (MD5) Previous issue date: 1976
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A Bayesian latent time-series model for switching temporal interaction analysis
We introduce a Bayesian discrete-time framework for switching-interaction analysis under uncertainty, in which latent interactions, switching pattern and signal states and dynamics are inferred from noisy and possibly missing observations of these signals. We propose reasoning over posterior …
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Financial Transfer and Its Impact on the Level of Democracy: A Pooled Cross-Sectional Time Series Model.
This dissertation is a pooled time series, cross-sectional, quantitative study of the impact of international financial transfer on the level of democracy. The study covers 174 developed and developing countries from 1976 through 1994. Through evaluating the democracy and democratization literature …
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NPL forecasting under a fourier residual modified model: An empirical analysis of an unsecured consumer credit provider in South Africa
… of domestic NPLs has led to a review of time series forecasting techniques. This dissertation explores whether a forecasting model combining a traditional time series approach with a Fourier series residual modification technique performs well in projecting NPLs. It also seeks to …
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Using Time Series Models for Defect Prediction in Software Release Planning
… a high-quality software release, sufficient time should be allowed for testing and fixing defects. Otherwise, there is a risk of slip in the development schedule and/or software quality. A time series model is used to predict the number of bugs created during development. The model depends on …
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Non-renewable resource price forecasting: a comparison of methods
… the ability of currently available forecasting models to predict non-renewable resource prices. This thesis compares two types of forecasting models used to predict non-renewable resource prices. Each model is assessed based upon theoretical and practical considerations. The models evaluated are …
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Investigating Economic Inequality And Voter Turnout In The Industrialized Democracies
… of 21 industrialized democracies using a pooled time series model of elections from 1970 to 1999. The findings demonstrate a connection between inequality and voter turnout wherein increases in inequality lead to reductions in voter turnout. The ramifications for democratic accountability and …
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Sustainable Intensification of Agriculture: Opportunities and Challenges for Food Security and Agrarian Adaptation to Environmental Change in Bangladesh
… using a spatial partial equilibrium trade model and a Life Cycle Assessment (LCA). The final article demonstrates a remote sensing methodology for monitoring dry season rice production at 30 m resolution in Bangladesh using a harmonic time series model, the Landsat archive, and Google Earth …
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Prediction of Enrollment using Computational Intelligence
… prediction has been considered as a form of time series prediction using CI techniques that include an artificial neural network (ANN), a neurofuzzy inference system (ANFIS) and an aggregated fuzzy time series model. A novel form of ANN, namely, single multiplicative neuron (SMN), as an …
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Trust, self-confidence, and operators' adaptation to automation
… allocation strategy. Specifically, an ARMAV time series model of the dynamic interaction of trust and self confidence, combined with individual biases, accounted for a between 60.9% and 86.5% of the variance in the use of the three automatic controllers. The third experiment replicated the …
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Maximum likelihood parameter estimation in time series models using sequential Monte Carlo
Time series models are used to characterise uncertainty in many real-world dynamical phenomena. A time series model typically contains a static variable, called parameter, which parametrizes the joint law of the random variables involved in the definition of the model. When a time series model is …
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Analysis of the dynamic nitrogen response of root and shoot transcripts in arabidopsis thaliana to gain insights on long-distance nitrogen signaling interactions
… often fall short of integrating data across time and space due to various biological constraints, while others attempt to use time series models not designed for biological systems. Here, I propose a new time series model that is suitable for biological systems, accounting for these …
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Modelling computer network traffic using wavelets and time series analysis
Modelling of network traffic is a notoriously difficult problem. This is primarily due to the ever-increasing complexity of network traffic and the different ways in which a network may be excited by user activity. The ongoing development of new network applications, protocols, and usage profiles …
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Practical Methods in Multivariate Time Series Analysis (Causality, Arma, Box-Jenkins)
… and Jenkins initiated the burgeoning interest in time series model building over a decade ago when they developed several specialized techniques used in model selection, estimation, and checking. These methods have been widely applied by researchers interested in lag structures, forecasts, and …
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Analysis of Continuous Longitudinal Data with ARMA(1, 1) and Antedependence Correlation Structures
… are often collected on individuals at scheduled times resulting in dependent responses. Inference methods for studying the behavior of responses over time as well as methods to study the association with certain risk factors or covariates taking into account the dependencies are of great …
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Imperfect competition and exchange rate pass-through in the international rice market
… and Thailand within certain market segments, a model of monopolistic price discrimination is developed in this study to examine export price adjustment in response to exchange rate fluctuations. The analysis is based on the ""pricing to market"" (PTM) model which postulates that tests for …
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Storage effects: the relationship between the hydrological dynamics of small infield pools and plant functional groups
… I investigated the habitat quality with a time series model which requires only the climatic time series evapotranspiration and precipitation and an observed daily water level time series. Further, I developed transfer function to describe mean drying up frequencies and mean spring high …
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A Modified Cluster-Weighted Approach to Nonlinear Time Series
… many applications involving data collected over time, it is important to get timely estimates and adjustments of the parameters associated with a dynamic model. When the dynamics of the model must be updated, time and computational simplicity are important issues. When the dynamic system is not …
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