Results 41 to 50 of about 229,123 (176)

On Nonparametric Hazard Estimation [PDF]

Journal of Biometrics & Biostatistics, 2015
The Nelson-Aalen estimator provides the basis for the ubiquitous Kaplan-Meier estimator, and therefore is an essential tool for nonparametric survival analysis. This article reviews martingale theory and its role in demonstrating that the Nelson-Aalen estimator is uniformly consistent for estimating the cumulative hazard function for right-censored ...
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A COMPARISON OF NONPARAMETRIC ESTIMATORS FOR LENGTH DISTRIBUTION IN LINE SEGMENT PROCESSES

Image Analysis and Stereology, 2019
We study nonparametric estimation of the length distribution for stationary line segment processes in the d-dimensional Euclidean space. Several methods have been proposed in the literature. We review different approaches (Horvitz-Thompson type estimator,
Zbynek Pawlas, Marketa Zikmundova
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Nonparametric estimation of mean-squared prediction error in nested-error regression models [PDF]

, 2016
Nested-error regression models are widely used for analyzing clustered data. For example, they are often applied to two-stage sample surveys, and in biology and econometrics.
Hall, Peter, Maiti, Tapabrata
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ANALISIS MODEL REGRESI NONPARAMETRIK SIRKULAR-LINEAR BERGANDA

E-Jurnal Matematika, 2016
Circular data are data which the value in form of vector is circular data. Statistic analysis that is used in analyzing circular data is circular statistics analysis.
KOMANG CANDRA IVAN, I WAYAN SUMARJAYA, MADE SUSILAWATI   +2 more
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Bayesian multivariate mixed-scale density estimation [PDF]

, 2014
Although continuous density estimation has received abundant attention in the Bayesian nonparametrics literature, there is limited theory on multivariate mixed scale density estimation.
Canale, Antonio, Dunson, David B.
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Empirical and Kernel Estimation of the ROC Curve

Acta Universitatis Lodziensis. Folia Oeconomica, 2015
The paper presents chosen methods for estimating the ROC (Receiver Operating Characteristic) curve, including parametric and nonparametric procedures.
Aleksandra Katarzyna Baszczyńska
doaj  

Model Selection for High Dimensional Nonparametric Additive Models via Ridge Estimation

Mathematics, 2022
In ultrahigh dimensional data analysis, to keep computational performance well and good statistical properties still working, nonparametric additive models face increasing challenges.
Haofeng Wang, Hongxia Jin, Xuejun Jiang, Jingzhi Li   +3 more
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Consistent estimation of the filtering and marginal smoothing distributions in nonparametric hidden Markov models [PDF]

, 2015
In this paper, we consider the filtering and smoothing recursions in nonparametric finite state space hidden Markov models (HMMs) when the parameters of the model are unknown and replaced by estimators.
Corff, Sylvain Le, De Castro, Yohann, Gassiat, Elisabeth   +2 more
core  

Nonparametric volatility density estimation

Bernoulli, 2003
We consider two kinds of stochastic volatility models. Both kinds of models contain a stationary volatility process, the density of which, at a fixed instant in time, we aim to estimate. We discuss discrete time models where for instance a log price process is modeled as the product of a volatility process and i.i.d. noise.
van Es, A.J., Spreij, P.J.C., van Zanten, J.H.   +2 more
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Nonparametric estimation in random sum models

Statistica, 2013
Let X1,X2,…,XN be independent, identically distributed, non-negative, integervalued random variables and let N be a non-negative, integer-valued random variable independent of X1,X2,…,XN .
Hassan S. Bakouch, Thomas A. Severini
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