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 43 for “"Parametric Estimation"”.
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Parametric estimation of superimposed signals
The problem of parametric estimation of signals composed of a weighted sum of functions drawn from a known parametric family with unknown parameters in white Gaussian noise was studied. New closed-form expressions of the Cramer-Rao bound (CRB) for parametric estimation of superimposed signals in …
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Non parametric Estimation of high-frequency Volatility and Correlation Dynamics
… of the Fourier estimator, a newly proposed nonparametric methodology to measure ex-post volatility and cross-volatilities as functions of time, when financial assets are observed at different highfrequency levels over the day. The estimator has the peculiar feature to employ the observed data …
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Parametric Estimation of the Heston Model under the Indirect Observability Framework
… the consistency and robustness of statistical estimation of parameters in the chosen stochastic model. Three parts are presented in this dissertation. In part I (Chapter 2) of this dissertation we show that the Method of Moments can be used to derive consistent and robust estimators when it is …
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Jointly Asymptotically Efficient Non-Parametric Estimation of Regression and Scale Parameters
Made available in DSpace on 2014-12-11T18:24:09Z (GMT). No. of bitstreams: 1 7414553.pdf: 1299803 bytes, checksum: f64de5f45cf8b17736390040f9111fbb (MD5) Previous issue date: 1974
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Mitigation of Interference From Iridium Satellites by Parametric Estimation and Subtraction
Radio astronomy is the science of observing the universe at radio frequencies. In recent years, radio astronomy has faced a growing interference problem as radio frequency (RF) bandwidth has become an increasingly scarce commodity. Communication systems such as Earth orbiting communication …
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Parametric Estimation of Stochastic Fading Channels and Their Role in Adaptive Radios
… Furthermore, computations of the best-known estimation techniques are often iterative, tedious, and complex. This thesis takes a renewed look at estimating fading parameters for the Nakagami-m, Rice-K, and Weibull distributions, specifically by showing that the need to solve transcendental …
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Non-parametric estimation methods for instrumental variables and sample selection : theory and applications
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Economics, 1998.
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Consistency and Convergence of Non-parametric Estimation of Drift and Diffusion Coefficients in SDEs from Long Stationary Time-series
We study the efficiency of non-parametric estimation of stochastic differential equations driven by Brownian motion (i.e. diffusions) from long stationary trajectories. First, we introduce estimators based on conditional expectation which is motivated by the definition of drift and diffusion …
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Data-driven Techniques For Estimation And Stochastic Reduction Of Multiscale Systems
Parametric estimation of stochastic processes is one of the most widely used techniques for obtaining effective models, given a discrete dataset. Often, the experimental or observational datasets are not explicitly generated by the underlying stochastic model and are, thus, expected to agree with …
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Query processing in heterogeneous distributed database management systems
… query expressed over a conceptual schema; (3) An estimation methodology to derive the intermediate result sizes of the database operations; (4) A query decomposition algorithm to generate an efficient sequence of the basic database operations to answer the query. This research addressed the first …
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Propulsion considerations for supersonic oblique flying wings
… computational tools (MSES), linearized theory, parametric estimation, and quasi D thermodynamic cycle analysis. Lift-to-drag ratio, thrust specific fuel consumption, and nacelle wave drag were examined as intermediate figures of merit that would ultimately impact the final performance …
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In-sample forecasting: structured models and reserving
… reserving practice can be understood as a non-parametric estimation approach in a structured model setting. The forecast of future claims is done without the use of exposure information, i.e., without knowledge about the number of underwritten policies. New statistical estimation techniques and …
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A function space approach to the generalized nonlinear model with applications to frequency domain spectral estimation
… (1983) outlined the theory of quasi-likelihood estimation in generalized linear models. Chiu (1988) showed that an iterated, reweighted least squares procedure applied to the periodogram produces estimates of spectral density model parameters for Gaussian univariate time series which have the …
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Parametric Modeling in the Presence of Measurement Error: Monte Carlo Corrected Scores
Parametric estimation is complicated when data are measured with error. The problem of regression modeling when one or more covariates are measured with error is considered in this paper. It is often the case that, evaluated at the observed error-prone data, the unbiased true-data estimating …
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ECONOMIC DIVERSIFICATION: THE CASE OF SAUDI ARABIA WITH REFERENCE TO RICH NATURAL RESOURCE COUNTRIES
… natural resource countries adapt the same non- parametric estimation results produced by Imb & Wacziarg (2003). Indeed, it will be interesting to investigate whether natural resource countries will have a u shape relationship between their level of diversification and their per capita revenue as …
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Signal parameter estimation methods: The non-eigenvector based approach
An idea behind this dissertation is the estimation of signal parameters of a radio channel snapshot. The focal point here to utilize the high resolution estimation capabilities of subspace based methods in association with non-eigenvector based parameter estimation methods to reduce the complexity …
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Systematic asset allocation using flexible views for South African markets
… 144, 145]. The HS-FP framework is a flexible non-parametric estimation approach that considers future asset class behavior to be conditional on time and market environments, and derives a forward-looking distribution that is consistent with this view while remaining as close as possible to the …
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What About Short Run?
… model to guide through the predictability estimation with much more efficiency gain. Finally I decompose the equity risk premium into two short-lived parts --- tail risk and diffusive risk --- and propose a semi-parametric estimation method for each part. The results are arranged in the …
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Essays in Economic *Growth and Asset Pricing
… specification in previous studies. Using semi-parametric estimation procedures we find ample evidence of pairwise convergence among 15 OECD countries. This result is contrary to the literature that uses unit roots and cointegration tests to analyze income convergence. In chapter 3, we propose a …
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