搜索结果: 1-15 共查到“Nonparametric Regression”相关记录22条 . 查询时间(0.145 秒)
Nonparametric Regression with Discrete Covariate and Missing Values
Nonparametric Regression Discrete kernel smoothing Imputation Missing Values Variance Reduction
2016/1/19
We consider nonparametric regression with a mixture of continuous and discrete ex-planatory variables where realizations of the response variable may be missing. An impu-tation based nonparametric reg...
Adaptive estimation in nonparametric regression with one-sided errors
adaptive convergence rates non-regular regression frontier estimation bandwidth selection Lepski's method minimax optimality Pickands estimator
2013/6/14
We consider the model of non-regular nonparametric regression where smoothness constraints are imposed on the regression function and the regression errors are assumed to decay with some sharpness lev...
Switching Nonparametric Regression Models and the Motorcycle Data revisited
nonparametric regression machine learning mixture of Gaussian processes latent variables EM algorithm motorcy-cle data
2013/6/14
We propose a methodology to analyze data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate...
Simultaneous L^2- and L^inf-Adaptation in Nonparametric Regression
Adaptive estimation nonparametric regression thresholding wavelets
2013/4/27
Consider the nonparametric regression framework. It is a classical result that the minimax rates for L^2- and L^inf-risk over a H\"older ball with smoothness index \beta are n^(-\beta/(2\beta+1)) and ...
Spatially-adaptive sensing in nonparametric regression
Nonparametric regression, adaptive sensing sequential design active learning spatial adaptation spatially-inhomogeneous functions.
2012/9/18
While adaptive sensing has provided improved rates of convergence in sparse regression and classication, results in nonparametric regres-sion have so far been restricted to quite specic classes of f...
Nonparametric Regression Estimation with Incomplete Data: Minimax Global Convergence Rates and Adaptivity
Adaptivity Besov spaces inhomogeneous data minimax estimation
2011/7/6
We consider the nonparametric regression estimation problem of recovering an unknown response function $f$ on the basis of incomplete data when the design points follow a known density $g$ with a fini...
Pointwise Adaptive M-estimation in Nonparametric Regression
adaptation Huber function Lepski's method M-estimation minimax estimation nonparametric regression robust estimation pointwise estimation
2011/6/17
This paper deals with the nonparametric estimation in heteroscedastic
regression Yi = f(Xi) + i; i = 1; : : : ; n, with incomplete information,
i.e. each real random variable i has a density gi wh...
Characteristic Function-Based Testing for Multifactor Continuous-Time Markov Models via Nonparametric Regression
Characteristic Function Markov models conditional distribution
2011/4/2
We develop a nonparametric regression-based goodness-of-fit test for multifactor continuous-time Markov models using the conditional characteristic function, which often has a convenient closed form o...
Characteristic Function-Based Testing for Multifactor Continuous-Time Markov Models via Nonparametric Regression
nonparametric regression economics and finance easy-to-interpret diagnostic procedures
2011/4/1
We develop a nonparametric regression-based goodness-of-fit test for multifactor continuous-time Markov models using the conditional characteristic function, which often has a convenient closed form o...
Tight conditions for consistent variable selection in high dimensional nonparametric regression
Tight conditions for consistent variable selection high dimensional nonparametric regression
2011/3/23
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of covariates is very large. The main focus is on the situation where the num...
Tight conditions for consistent variable selection in high dimensional nonparametric regression
variable selection high dimensional nonparametric regression
2011/3/22
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of covariates is very large. The main focus is on the situation where the nu...
Nonparametric regression with filtered data
censoring counting process theory hazard functions kernel estimation local linear estimation truncation
2011/3/21
We present a general principle for estimating a regression function nonparametrically, allowing for a wide variety of data filtering, for example, repeated left truncation and right censoring. Both th...
Nonparametric Regression With Nearly Integrated Regressors Under Long Run Dependence
Asymptotics kernel smoothing local time of an Ornstein-Uhlenbeck fractional Brownian motion nonlinearity nonstationary covariates unit root
2011/4/2
We study nonparametric estimation of regression function with nonstationary (integrated or nearly integrated) covariates and the error series of the regressor process following a fractional ARIMA mode...
Testing Parallelism of Nonparametric Regression Curves
Testing Parallelism Nonparametric Regression Curves
2010/10/19
This paper considers the inference of regression functions in the context of multiple time series. For an arbitrary number of time series observed at a large number of time points, we test the hypoth...
Adaptive asymptotically efficient estimation in heteroscedastic nonparametric regression
asymptotic bounds adaptive estimation efficient estimation het-eroscedastic regression nonparametric regression Pinsker’s constant
2010/3/10
The paper deals with asymptotic properties of the adaptive proce-
dure proposed in the author paper, 2007, for estimating an unknown
nonparametric regression. We prove that this procedure is asympto...