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Showing 1 to 20 of 120 for “"quantiles"”.
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Binary Regression Quantiles
Binary regression quantiles are solutions to difficult optimization problems that requires the use of a global optimizer. Chapter 5 reviews some of the literature on simulated annealing, a method widely used in a diverse array of fields to solve demanding optimization problems.
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Three Essays on Extremal Quantiles
<p>Extremal quantile index is a concept that the quantile index will drift to zero (or one)</p><p>as the sample size increases. The three chapters of my dissertation consists of three</p><p>applications of this concept in three distinct econometric problems. In Chapter 2, I</p><p>use the concept of …
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Space-time estimation of flood quantiles
L'abstract è presente nell'allegato / the abstract is in the attachment
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A Partly Linear Model for Censored Regression Quantiles
… a partly linear model for censored regression quantiles as a method for modeling nonlinearities in duration data. As quantile regression does not impose a proportionality constraint on the hazard, it is less restrictive than the Cox method and it often illuminates aspects of the data that could …
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Effective Estimation of Marginal Quantiles in Steady-State Simulations
… Time Series (STS) for estimating steady-state quantiles with confidence intervals having given coverage probability and, potentially precision; and (2) the development and experimental evaluation of three automated methods for effective estimation of marginal quantiles in steady-state …
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Some topics on robust nonparametric regression and regression quantiles
Local kernel estimates and B-spline estimates are considered in the nonparametric regression and the 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 …
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LIMIT THEOREMS FOR FUNCTIONS OF MARGINAL QUANTILES AND ITS APPLICATION.
… the limit theorem for functions of marginal quantiles.We mainly studied how to explore multivariate distribution using the joint distribution of marginal quantiles. Limit theory for the mean of functions of order statistics is presented. The result include multivariate central theorem and …
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Variance reduction techniques for estimating quantiles and value-at-risk
Quantiles, as a performance measure, arise in many practical contexts. In finance, quantiles are called values-at-risk (VARs), and they are widely used in the financial industry to measure portfolio risk. When the cumulative distribution function is unknown, the quantile can not be computed exactly …
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Learned Interpolation for Better Streaming Quantiles with Worst Case Guarantees
… apply interpolation techniques to the streaming quantiles problem to attempt to achieve better approximations on real-world data sets than KLL while maintaining similar guarantees in the worst case.
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SEMIPARAMETRIC METHODS IN THE ESTIMATION OF TAIL PROBABILITIES AND EXTREME QUANTILES
… threshold exceedance probabilities and extreme quantiles arise ubiquitously in bio-surveillance, economics, natural disaster insurance actuary, quality control schemes, etc. A useful way to make an assessment of extreme events is to estimate the probabilities of exceeding large threshold values …
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Randomization-based inference for distributions and quantiles of individual treatment effects
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01
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Approximation of Quantiles of Rank Test Statistics Using Almost Sure Limit Theorems
… of Berkes and Csaki (2001), and it estimates the quantiles of a test statistic using only the data. To date, LQE has been used in only a few applications. We extend the use of LQE to three widely analyzed problems.</p> <p>We investigate the LQE approach using fully nonparametric rank statistics to …
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One and Two-Step Estimation of Time Variant Parameters and Nonparametric Quantiles
… 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 aggregating data by an explanatory variable such as time and smoothing the …
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Prediction of Conditional Quantiles in Ordinal Regression With Applications to Aging Research
Key words: Ordinal data; Quantile regression; Nonparametric transformation model; Second Longitudinal Study of Aging.
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Sequential estimation of quantiles and adaptive sequential estimation of location and scale parameters
Made available in DSpace on 2011-05-07T13:30:18Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9114359.pdf: 2918189 bytes, checksum: a86ffe3dce26cf9fb66ab0d60116692e (MD5) Previous issue date: 1990
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Statistical inference for residual time quantiles in regression models for censored time-to-event data
… since time zero. We develop methods to estimate quantiles of residual time under a few different settings: the Cox proportional hazards model (with fixed and with external time-varying covariates) and the additive hazards model. In each setting, we consider point estimation, asymptotic …
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Robust sensitivity analysis for quantiles of hidden biases and treatment effects in matched observational studies
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01
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Water Level Quantiles Of Devils Lake Under Down-Scaled Gcm Predictions Using A Coupled Hydro-Climatic Model
<p>The research focuses in calibrating a coupled rainfall-runoff model and a reservoir model for the Devils Lake using data from both ground gage stations and NASA satellite observations. The purpose is to determine the feasibility of using spatially distributed GCM data with a well calibrated …
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Modélisation univariée et multivariée des extrêmes avec covariables
… de trois approches pour l'estimation des quantiles conditionnels. II s'agit des modèles de régression avec des fonctions de perte asymétriques, le modèle GEV avec covariables et les modèles multivariés basés sur les copules vine. L'équivalence de l'approche de la régression …
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Semiparametric Estimation of Binary Response Valuation Models
… that KSE welfare measures are closer to the quantiles approach than the standard logit. However, the differences in the welfare measures suggest that the KSE fail to capture all the structure revealed in the quantiles regression analysis.
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