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Sparse Estimation And Inference For Censored Median Regression
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Book Synopsis Sparse Estimation and Inference for Censored Median Regression by : Justin Hall Shows
Download or read book Sparse Estimation and Inference for Censored Median Regression written by Justin Hall Shows and published by . This book was released on 2009 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: censored data, median regression, variable selection.
Book Synopsis Sparse Estimation and Inference for Censored Median Regression by :
Download or read book Sparse Estimation and Inference for Censored Median Regression written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Censored median regression models have been shown to be useful for analyzing a variety of censored survival data with the robustness property. We study sparse estimation and inference of censored median regression. The new method minimizes an inverse censoring probability weighted least absolute deviation subject to the adaptive LASSO penalty. We show that, with a proper choice of the tuning parameter, the proposed estimator has nice theoretical properties such as root-n consistency and asymptotic normality. The estimator can also identify the underlying sparse model consistently. We propose using a resampling method to estimate the variance of the proposed estimator. Furthermore, the new procedure enjoys great advantages in computation, since its entire solution path can be obtained efficiently. Also, the method can be extended to multivariate survival data, where there is a natural or artificial clustering structure. The performance of our estimator is evaluated by extensive simulations and two real data applications.
Book Synopsis Handbook of Quantile Regression by : Roger Koenker
Download or read book Handbook of Quantile Regression written by Roger Koenker and published by CRC Press. This book was released on 2017-10-12 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments. The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.
Book Synopsis Semiparametric Estimation and Inference for Censored Regression Models by : Lei Pang
Download or read book Semiparametric Estimation and Inference for Censored Regression Models written by Lei Pang and published by . This book was released on 2012 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Methods at the Forefront of Biomedical Advances by : Yolanda Larriba
Download or read book Statistical Methods at the Forefront of Biomedical Advances written by Yolanda Larriba and published by Springer Nature. This book was released on 2023-08-09 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents novel statistics methods and reproducible software that helps to solve challenging problems in biomedicine. Specifically, it consists of a collection of 11 chapters contributed by some of the leading experts in the mathematical and statistical field which address new challenges in very disparate biomedical areas, such as genomics, cancer, circadian biology, microbiome, mental disorders, and more. The mathematical rigor is written in a user-friendly way to serve a general biomedical audience ranging from trainees or students to doctors, as well as scientific researchers, university departments, and PhD students.
Book Synopsis On Nonparametric Estimation and Inference with Censored Data, Bandwidth Selection for Local Polynomial Regression, and Subset Selection in Explanatory Regression Analyses by : Derick Randall Peterson
Download or read book On Nonparametric Estimation and Inference with Censored Data, Bandwidth Selection for Local Polynomial Regression, and Subset Selection in Explanatory Regression Analyses written by Derick Randall Peterson and published by . This book was released on 1998 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Variable Screening and Model Selection in Censored Quantile Regression Via Sparse Penalties and Stepwise Refinement by :
Download or read book Variable Screening and Model Selection in Censored Quantile Regression Via Sparse Penalties and Stepwise Refinement written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Inference for High-dimensional Left-censored Linear Model and High-dimensional Precision Matrix by : Jiaqi Guo
Download or read book Inference for High-dimensional Left-censored Linear Model and High-dimensional Precision Matrix written by Jiaqi Guo and published by . This book was released on 2018 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the first two chapters, we consider inference for high-dimensional left-censored linear models. Left-censored data arises from measurement limits in scientific devices and social science data. We consider the problem of constructing confidence intervals for the parameters in left-censored linear models. In Chapter 1, we present smoothed estimating equations (SEE) and smoothed robust estimating equations(SREE) frameworks that are adaptive to censoring level and are more robust to misspecification of the error distribution. In Chapter 2, we study inference problem for parameters in high-dimensional left-censored quantile regression model. We modify the quantile loss to accommodate the left-censored nature of the problem, by extending the idea of redistribution of mass. Furthermore, applying the de-biasing technique to the initial estimator leads to an improved estimator suitable for high-dimensional inference under left-censored quantile regression setting. For both problems, asymptotic properties have been investigated. In Chapter 3, we devise a projection pursuit testing procedure for generalized hypotheses on high-dimensional precision matrix. We illustrate the procedure under specific examples of hypotheses: testing for row sparsity, minimum signal strength, bandedness and generalized bandedness. We demonstrate the performance of the testing procedure through extensive numerical experiments, and present the findings for two real datasets.
Book Synopsis Two-step Quantile Estimation of the Censored Regression Model by : James Powell
Download or read book Two-step Quantile Estimation of the Censored Regression Model written by James Powell and published by . This book was released on 1986 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bias-corrected Quantile Regression Estimation of Censored Regression Models by : Pavel Čížek
Download or read book Bias-corrected Quantile Regression Estimation of Censored Regression Models written by Pavel Čížek and published by . This book was released on 2014 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Regression Models by : Richard Breen
Download or read book Regression Models written by Richard Breen and published by SAGE. This book was released on 1996-01-09 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the regression models needed, where an outcome variable for a sample is not representative of the population from which a generalized result is sought.
Book Synopsis Simple Three-step Censored Quantile Regression and Extramartial Affairs by : Victor Chernozhukov
Download or read book Simple Three-step Censored Quantile Regression and Extramartial Affairs written by Victor Chernozhukov and published by . This book was released on 2001 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper suggests simple 3- and 4-step estimators for censored quantile regression models with an envelope or a separation restriction on the censoring probability. The estimators are theoretically attractive (asymptotically as efficient as the celebrated Powell's censored least absolute deviation estimator). At the same time, they are conceptually simple and have trivial computational expenses. They are especially useful in samples of small size or models with many regressors, with desirable finite sample properties and small bias. The envelope restriction costs a small reduction of generality relative to the canonical censored regression quantile model, yet its main plausible features remain intact. The estimator can also be used to estimate a large class of traditional models, including normal Amemiya-Tobin model and many accelerated failure and proportional hazard models. The main empirical example involves a very large data-set on extramarital affairs, with high 68 percent censoring. We estimate 45-90 percent conditional quantiles. Effects of covariates are not representable as location-shifts. Less religious women, with fewer children, and higher status, tend to engage into the matters relatively more than their opposites, especially at the extremes. Marriage longevity effect is positive at moderately high quantiles and negative at high quantiles. Education and marriage happiness effects are negative, especially at the extremes. We also briefly consider the survival quantile regression on the Stanford heart transplant data. We estimate the age and prior surgery effects across survival quantiles. Keywords: Quantile regression, median regression, censoring, duration, survival, classification, discriminant analysis. JEL Classifications: C14, C24, C41, C51, D13.
Book Synopsis Censored Quantile Regression with Auxiliary Information by : Chithran Vadaverkkot Vasudevan
Download or read book Censored Quantile Regression with Auxiliary Information written by Chithran Vadaverkkot Vasudevan and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In Survival analysis, it is vital to understand the effect of the covariates on the survival time. Commonly studied models are the Cox [1972] proportional hazards model and the accelerated failure time model. These methods mainly focus on one characteristic of the survival time. In reality, the association between the response and risk factors is not homogeneous always. This leads to the use of quantile regression [Koenker and Basset, 1978] models, which provide a global description of the association. In quantile regression modeling of the survival data, the problem of estimating the regression coefficients for extreme quantiles can be affected by severe censoring [Portnoy, 2003], especially when the sample size is small. In epidemiological studies, however, there are often times when only a subset of the whole study cohort is accurately observed. The rest of the cohort has only some auxiliary covariate available. The naive use of the auxiliary covariate in the model without the accurately measured covariate could lead to biased estimates. To deal with this problem in censored quantile regression, we propose a regression calibration based method when there is a linear relationship between the auxiliary covariate and the accurately measured covariate. When the relationship is non-linear, we propose a non-parametric kernel smoothing technique. We also propose an empirical likelihood [Owen, 1998, 2001] based weighted censored quantile regression to improve the efficiency of the censored quantile regression estimation by utilizing the auxiliary information about the target population parameters available through scientific facts/previous studies. The proposed estimators are consistent and have asymptotically Gaussian distributions. The efficiency gain compared to the existing methods is remarkable. These methods provide the possibilities of looking into extreme quantiles of the survival distribution. We also applied our proposed methods in real case examples.
Book Synopsis Essays on Estimation of Censored Quantile Regression for Cross-sectional and Panel Data by : Qian Wang
Download or read book Essays on Estimation of Censored Quantile Regression for Cross-sectional and Panel Data written by Qian Wang and published by . This book was released on 2016 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Quantile regression with censoring and endogeneity by : Victor Chernozhukov
Download or read book Quantile regression with censoring and endogeneity written by Victor Chernozhukov and published by . This book was released on 2011 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator combines Powell (1986) censored quantile regression (CQR) to deal semiparametrically with censoring, with a control variable approach to incorporate endogenous regressors. The CQIV estimator is obtained in two stages that are nonadditive in the unobservables. The first stage estimates a nonadditive model with infinite dimensional parameters for the control variable, such as a quantile or distribution regression model. The second stage estimates a nonadditive censored quantile regression model for the response variable of interest, including the estimated control variable to deal with endogeneity. For computation, we extend the algorithm for CQR developed by Chernozhukov and Hong (2002) to incorporate the estimation of the control variable. We give generic regularity conditions for asymptotic normality of the CQIV estimator and for the validity of resampling methods to approximate its asymptotic distribution. We verify these conditions for quantile and distribution regression estimation of the control variable. We illustrate the computation and applicability of the CQIV estimator with numerical examples and an empirical application on estimation of Engel curves for alcohol
Book Synopsis Estimators and Inference in a Censored Regression Model with Endogenous Covariates by :
Download or read book Estimators and Inference in a Censored Regression Model with Endogenous Covariates written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Simple 3-Step Censored Quantile Regression and Extramarital Affairs by : Victor Chernozhukov
Download or read book Simple 3-Step Censored Quantile Regression and Extramarital Affairs written by Victor Chernozhukov and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper suggests simple 3- and 4-step estimators for censored quantile regression models with an envelope or a separation restriction on the censoring probability. The estimators are theoretically attractive (asymptotically as efficient as the celebrated Powell's censored least absolute deviation estimator). At the same time, they are conceptually simple and have trivial computational expenses. They are especially useful in samples of small size or models with many regressors, with desirable finite sample properties and small bias. The envelope restriction costs a small reduction of generality relative to the canonical censored regression quantile model, yet its main plausible features remain intact. The estimator can also be used to estimate a large class of traditional models, including normal Amemiya-Tobin model and many accelerated failure and proportional hazard models. The main empirical example involves a very large data-set on extramarital affairs, with high 68 percent censoring. We estimate 45-90 percent conditional quantiles. Effects of covariates are not representable as location-shifts. Less religious women, with fewer children, and higher status, tend to engage into the matters relatively more than their opposites, especially at the extremes. Marriage longevity effect is positive at moderately high quantiles and negative at high quantiles. Education and marriage happiness effects are negative, especially at the extremes. We also briefly consider the survival quantile regression on the Stanford heart transplant data. We estimate the age and prior surgery effects across survival quantiles.
