Listar 1. Investigación por título
Mostrando ítems 6722-6741 de 10124
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Nonparametric estimation of the conditional variance function with correlated errors
(Taylor & Francis, 2006) -
Nonparametric Conditional Risk Mapping Under Heteroscedasticity
(Springer Nature, 2024-03)[Absctract]: A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that ... -
Nonparametric covariate hypothesis tests for the cure rate in mixture cure models
(John Wiley & Sons, 2020-06)[Abstract]: In lifetime data, like cancer studies, there may be long term survivors, which lead to heavy censoring at the end of the follow-up period. Since a standard survival model is not appropriate to handle these data, ... -
Nonparametric Density and Regression Estimation for Samples of Very Large Size
(2021)[Abstract] This dissertation mainly deals with the problem of bandwidth selection in the context of nonparametric density and regression estimation for samples of very large size. Some bandwidth selection methods have ... -
Nonparametric estimation for a functional-circular regression model
(Springer, 2024)[Abstract]: Changes on temperature patterns, on a local scale, are perceived by individuals as the most direct indicators of global warming and climate change. As a specific example, for an Atlantic climate location, spring ... -
Nonparametric Estimation in Mixture Cure Models with Covariates
(Springer Nature, 2023-05-17)[Abstract] Nonparametric estimation methods for the cure rate and the distribution of the failure time of uncured subjects with covariates for censored survival data have attracted much attention in the last few years. To ... -
Nonparametric estimation of circular trend surfaces with application to wave directions
(2021)In oceanography, modeling wave fields requires the use of statistical tools capable of handling the circular nature of the data measurements. An important issue in ocean wave analysis is the study of height and direction ... -
Nonparametric estimation of the probability of default in credit risk.
(2022)[Abstract] Financial institutions are interested in knowing the probability that their clients declare themselves unable to pay the debts incurred by granting a credit. The aim of this work is to propose models to estimate ... -
Nonparametric forecasting in time series: a comparative study
(Taylor & Francis, 2007)The problem of predicting a future value of a time series is considered in this paper. If the series follows a stationary Markov process, this can be done by nonparametric estimation of the autoregression function. Two ... -
Nonparametric geostatistical risk mapping
(2018)In this work, a fully nonparametric geostatistical approach to estimate threshold exceeding probabilities is proposed. To estimate the large-scale variability (spatial trend) of the process, the nonparametric local linear ... -
Nonparametric incidence estimation and bootstrap bandwidth selection in mixture cure models
(Elsevier, 2017-01)[Abstract]: A completely nonparametric method for the estimation of mixture cure models is proposed. A nonparametric estimator of the incidence is extensively studied and a nonparametric estimator of the latency is presented. ... -
Nonparametric Inference for Big-But-Biased Data
(2021)[Abstract] It is often believed that in a Big Data context, given the large amount of data available, the data re ect precisely the underlying population. However, the data are often strongly biased due to the procedure ... -
Nonparametric Inference for Mixture Cure Model When Cure Information Is Partially Available
(MDPI, 2021)[Abstract] We introduce nonparametric estimators to estimate the conditional survival function, cure probability and latency function in the setting of a mixture cure model when the cure status is partially known. For the ... -
Nonparametric inference for neural synchrony under low firing activity
(2013)[Abstract] The aim of this thesis is to introduce statistical tools to study neural synchrony under spontaneous activity. The data analyzed comes from extracellular recordings of the primary visual cortex of anesthetized ... -
Nonparametric Inference for Regression Models with Spatially Correlated Errors
(2020)[Abstract] Regression estimation can be approached using nonparametric procedures, producing exible estimators and avoiding misspeci cation problems. Alternatively, parametric methods may be preferable to nonparametric ... -
Nonparametric Inference for the Mixture Cure Model When the Cure Status is Partially Known
(2022)[Abstract] Classical analysis of time-to-event data assumes that all individuals will eventually experience the event of interest. However, when there is evidence of long-term survivors, cure models should be used ... -
Nonparametric Inference in Mixture Cure Models
(2018)[Abstract] A completely nonparametric method for the estimation of mixture cure models is proposed. An incidence estimator is extensively studied and a latency estimator is presented. These estimators, which are based ... -
Nonparametric Inference in Mixture Cure Models
(MDPI, 2018-09)[Abstract]: A completely nonparametric method for the estimation of mixture cure models is proposed. Nonparametric estimators for the cure probability (incidence) and for the survival function of the uncured population ... -
Nonparametric Kernel Estimation of the Probability of Cure in a Mixture Cure Model when the Cure Status is Partially Observed
(Sage, 2022-08-01)[Abstract] Cure models are a class of time-to-event models where a proportion of individuals will never experience the event of interest. The lifetimes of these so-called cured individuals are always censored. It is usually ... -
Nonparametric latency estimation for mixture cure models
(Springer Nature, 2017-06)[Abstract]: A nonparametric latency estimator for mixture cure models is studied in this paper. An i.i.d. representation is obtained, the asymptotic mean squared error of the latency estimator is found, and its asymptotic ...