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 “"Asymptotic normality"”.
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Enumeration Results On Leaf Labeled Trees
… or species trees we show the asymtotic normality of categories of phylogenetic trees. P.L. Erdos and L.A. Szekely [Adv. Appl. Math.series 10,1989, 488--496] gave a bijection between rooted semilabeled trees and set partitions. L.H. Harper's results [Ann. Math.Stat.series 38, 1967, …
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Quantile regression and the duration of unemployment
… Both the $N\sp{1/2}$-consistency and the asymptotic normality of quantile estimator are derived for nonlinear regression models. The proof of asymptotic normality is based on the approach introduced by Pollard (1989) using maximal inequalities and quadratic approximation to the objective …
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Performance of Bootstrap Confidence Region For Binomial Distribution With Unknown Parameters p and m
… Thus, the Delta Method is used to derive the asymptotic normality of the joint distribution of the Method of Moments estimators. After finding the estimators pˆ, and mˆ , I will work on the Asymptotic Normality of the Estimators. For Asymptotic Normality of the Estimators by method of moment, …
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Some topics on robust nonparametric regression and regression quantiles
… generalized linear models. The consistency and asymptotic normality of kernel estimates are proved. Simulations on B-spline estimates for nonparametric regression and generalized linear models are provided.
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Nonparametric function smoothing: fiducial inference of free knot splines and ecological applications
… we then derive conditions sufficient to for asymptotic normality of the multivariate fiducial density. We then derive the fiducial density for an arbitrary degree spline with an arbitrary number of knot points. We then show that free-knot splines of degree 3 or greater satisfy the asymptotic …
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Maximum empirical likelihood estimation in U-statistics based general estimating equations
… (JEL) approach. We give the local uniform asymptotic normality condition for the log-JEL for UGEE's. We derive the estimating equations for finding MELE's and provide their asymptotic normality. We obtain easy MELE's which have less computational burden than the usual MELE's and can be …
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Likelihood Theory and Methods for Generalized Linear Mixed Models
… Existing theoretical results available for the asymptotic variance-covariance matrix for such estimators contain limits and expectations over the response distribution, hence such results are not in ready-to-use forms when carrying out tasks such as constructing studentized confidence intervals …
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Limit Theorems for Processes and Stopping Rules in Adaptive Sequential Estimation
This thesis deals with the asymptotic behavior of stopping rules ${\rm T\sb{A}}$ and ${\rm T\sb{d}}$ proposed by Martinsek (Ann. Statist., 12 (1984):533-550). The asymptotic normality of these stopping rules, when A tends to infinity and d tends to zero respectively, is proved. In the course of …
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On Logistic Regression Approach to Survival Data and Power Divergence Statistics for Life Tables
… are consistent and their corresponding asymptotic normality results also hold. Extension of Efron's method to regression model is proposed and their asymptotic properties again are examined.
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Estimating partial group delay
… approaches. Conditions for weak consistency and asymptotic normality of the proposed estimators are obtained. Applications to a multiple test of partial group delay are investigated. The time lag interpretation of partial group delay is justified, which provides insight into the nature of linear …
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Statistical analysis for discretely observed Lévy processes
… when t tends to zero. Then, we prove local asymptotic normality under different sampling schemes and conditions on the Lévy measure, including stable, Gamma, Normal inverse Gaussian and generalized hyperbolic Lévy processes. Furthermore, we apply our results to martingale estimating …
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Contributions to Semiparametric Inference to Biased-Sampled and Financial Data
… and achieve a gain in efficiency. The usual asymptotic properties, including consistency and asymptotic normality, are established under suitable regularity conditions. We performed simulation and case studies to demonstrate the feasibility and effectiveness of the proposed method. The second …
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LINEAR HYPOTHESIS TESTING FOR HIGH-DIMENSIONAL DATA UNDER HETEROSCEDASTICITY
… Theoretical properties of our tests, such as asymptotic normality and power, are established. Simulation studies and real data examples are also presented to demonstrate the good performance of our tests.
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Some issues in item response theory
… procedure by using a kernel smoothing technique. Asymptotic normality of the test statistic is given and proved, which in turn justifies our procedure. Simulation studies show the procedure works well for the case of large examinee sample sizes. Some Graduate Record Examination (GRE) verbal test …
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Advances in Sobol' Index Estimation: Metamodeling, Multilevel Monte Carlo Metamodeling, and Nested Simulation Techniques
… estimators for Sobol' indices with established asymptotic normality, enabling reliable uncertainty quantification. Our proposed MLMC metamodeling approach for variance function estimation substantially reduces computational complexity, yielding competitive estimators with superior performance. …
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Aukšto dažnio duomenų agregavimas ir vertės pokyčio rizika /
… estimators of model parameters consistency and asymptotic normality are proved; the analysis of residuals is provided. In the last chapter of the thesis the empirical study about Hurst index intraday value dependence on data aggregation taking different foreign currencies’ absolute returns is …
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Essays on Optimal Transport Theory and Causal Inference: A Theoretical and Empirical Approach
… region. We establish the consistency and asymptotic normality of the proposed estimators under high-level assumptions on the estimator of the optimal transport map. Three examples of the estimator of the optimal transport map are studied in detail and are shown to satisfy the high-level …
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Likelihood-based testing and model selection for hazard functions with unknown change-points
… continuous hazard functions using local asymptotic normality (LAN). Finally we generalize our earlier results for abrupt changes to include covariate information using the LAN techniques. While we focus on the cases of no censoring, simple right censoring, and censoring generated by …
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Some properties of the sample coefficient of variation
… Cramer also shows that this distribution is asymptotically normal. Using Fisher's k statistics approximations to the mean and next three central moments of the S.C.V., are obtained through the 1/n<sup>3</sup> terms. Investigations for the normal and gamma parent cases are then undertaken. The …
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Endogeneity and Sampling of Alternatives in Spatial Choice Models
… to achieve consistency, relative efficiency, and asymptotic normality when the underlying model belongs to the Multivariate Extreme Value class. This development allows for the estimation of spatial choice models with more realistic error structures. Monte Carlo experiments and real data from …
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