NDLTD logo NDLTD Union Catalog and Global ETD Search

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.

Results

Showing 1 to 18 of 18 for “"bandwidth selection"”.

  1. Optimal bandwidth selection rule for kernel regression estimator with dependent variables

    Kim, Tae YoonUniversity of Illinois at Urbana-Champaign2011

    … in applying a kernel estimator is the choice of bandwidth. The main purpose of this work is to establish asymptotic optimality for a bandwidth selection rule under dependence which can be interpreted in terms of cross validation. In addition, some moment bounds for dependent variables will be …

    uiuc Repository record

  2. A BAYESIAN APPROACH FOR BANDWIDTH SELECTION IN KERNEL DENSITY ESTIMATION WITH CENSORED DATA

    Kuruwita, Chinthaka

    clemson Repository record

  3. Bandwidth Selection Concerns for Jump Point Discontinuity Preservation in the Regression Setting Using M-smoothers and the Extension to hypothesis Testing

    Burt, David AllanVirginia Tech2000

    … can be used in practice the choice of the bandwidth parameters must be addressed. The jump preserving M-smoother requires two bandwidth parameters h and g. These two parameters determine the amount of noise that is smoothed out as well as the size of the jumps which are preserved. If these …

    vt Repository record

  4. Bandwidth Selection for Level Set Estimation in the Context of Regression and a Simulation Study for Non Parametric Level Set Estimation When the Density Is Log-Concave

    Gonzalez Martinez, Gabriela2022

    Bandwidth selection is critical for kernel estimation because it controls the amount of smoothing for a function's estimator. Traditional methods for bandwidth selection involve optimizing a global loss function (e.g. least squares cross validation, asymptotic mean integrated squared error). …

    york Repository record

  5. CROSS VALIDATION METHOD ON WEIGHTED ISOTONIC REGRESSION FOR NONPARAMETRIC REGRESSION FITTING

    ZHANG YIWEN2017

    … of X. Considering the importance of the bandwidth selection for nonparametric fitting, a new Cross Validation (CV) method that incorporates the non-decreasing condition is proposed. Furthermore, the simulations are conducted to evaluate the performance of this CV method in comparison with …

    nus Repository record

  6. Kernel Estimators in Complex Data Analysis

    Weng, Guangwei2021

    … of kernel estimators. In Chapter 2, we develop a bandwidth (matrix) selector for multivariate kernel density estimators of level sets and highest density regions. We consider a different loss function from the one used in classical bandwidth selection problem and derive an asymptotic approximation …

    umn Repository record

  7. Smooth regression quantile estimation

    Yu, KemingThe Open University1997

    … real applications. I include algorithmdesign and selection of smoothing parameters. Chapter 2 studies two estimators, first a single-kernel estimator based on "check function" and a bandwidth selection rule is proposed based on the asymptotic MSE of this estimator. Second a recursive double-kernel …

    the-open-u Repository record

  8. Practical Aspects Of Kernel Smoothing For Binary Regression And Density Estimation

    Signorini, David F.The Open University1998

    … are examined in detail, and extended to two bandwidth cases. The asymptotic behaviour of these estimators is presented in a unified way, and the practical performance is assessed using a simulation experiment. It is shown that, when using the ideal bandwidth, the two bandwidth estimators …

    the-open-u Repository record

  9. ENHANCING pm2.5 AIR POLLUTION ANALYSIS IN BEIJING: A TRANSITION FROM NON-PARAMETRIC REGRESSION TO ADVANCED MACHINE LEARNING METHODOLOGY

    ZENG ZITONG2024

    … which used non-parametric regression and bandwidth selection frequency, to assess PM2.5 levels as well as feature importance, may result in overfitting, lack of interpretability and computational inefficiency. Our research aims to address these limitations by making use of the RF+ …

    nus Repository record

  10. Improving partial mutual information based input variable selection for data driven environmental and water resources models

    Li, Xuyuan2015

    … data collection, data processing, input variable selection, data division, calibration and validation, are vitally important, as ANN model development is based on data, rather than understanding of the underlying physical processes. Among these methods, input variable selection (IVS) plays a …

    adelaide Repository record

  11. Estimating Non-homogeneous Intensity Matrices in Continuous Time Multi-state Markov Models

    Lebovic, Gerald2011

    … In addition, model assessment tools such as bandwidth selection, grid size selection, and bootstrapped percentile intervals are examined. Lastly, the method is applied to an HIV data set to examine the intensities with regard to depression scores. Although computationally intensive, it …

    toronto-retro Repository record

  12. Image Segmentation and Robust Estimation Using Parzen Windows

    Singh, Maneesh KumarUniversity of Illinois at Urbana-Champaign2015

    … A novel plug-in estimator is proposed for the bandwidth (scale) of the window kernels. Asymptotic optimality of the proposed bandwidth is proved. The bandwidth selection scheme is validated for segmentation of real images. The density estimation framework is extended to model more structured …

    uiuc Repository record

  13. Three Essays on Econometric Analysis

    Zheng, ZhiyuanVirginia Tech2011

    … of methods, the least square cross-validated bandwidth selection procedure and the conventional nonparametric significance testing frameworks. In chapter 3, a bootstrap test statistic is proposed to test the validity of imposing some arbitrary restrictions on higher order derivatives of a …

    vt Repository record

  14. On Variable Bandwidth Kernel Density And Regression Estimation

    Nakarmi, Janet2019

    We study the ideal variable bandwidth kernel density estimator introduced by McKay (1993) and the plug-in practical version of the variable bandwidth kernel density estimator with two sequences of bandwidths as in Ginè and Sang (2013).We estimate the variance of the variable bandwidth kernel …

    mississippi Repository record

  15. Estimation and Testing Methods for Monotone Transformation Models

    Zhang, Junyi2013

    … The self-induced smoothing does not require bandwidth selection, yet provides the right amount of smoothness so that the estimator is asymptotically normal with mean zero (unbiased) and variance-covariance matrix consistently estimated by the usual sandwich-type estimator. An iterative …

    columbia-diss Repository record

  16. Nonparametric Modelling for Directional Data

    Xu, DanliResearchSpace@Auckland2022

    … for usual statistical problems such as feature selection is provided. In this thesis, we present density estimators for the above three categories of directional observations under the framework of mixture models. Density estimation is a vital aspect in data analysis. It examines important …

    auckland-ms Repository record

  17. Local Adaptive Smoothing in Kernel Regression Estimation

    Zheng, Qi

    clemson Repository record

  18. One and Two-Step Estimation of Time Variant Parameters and Nonparametric Quantiles

    Gadidov, Bogdan2019

    <p>This dissertation develops and discusses several one-step and two-step smoothing methods of time variant nonparametric quantiles and time variant parameters from probability models. First, we investigate and develop nonparametric techniques for measuring extreme quantiles. The method involves …

    kennesaw Repository record