ListarGI-MODES - Artigos por tema "Bootstrap"
Mostrando ítems 1-20 de 20
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A goodness-of-fit test for regression models with spatially correlated errors
(2020)The problem of assessing a parametric regression model in the presence of spatial correlation is addressed in this work. For that purpose, a goodness-of-fit test based on a -distance comparing a parametric and nonparametric ... -
Big-But-Biased Data Analytics for Air Quality
(MDPI AG, 2020-09-22)[Abstract] Air pollution is one of the big concerns for smart cities. The problem of applying big data analytics to sampling bias in the context of urban air quality is studied in this paper. A nonparametric estimator ... -
Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation
(MDPI, 2022)[Abstract] For a fixed time, t, and a horizon time, b, the probability of default (PD) measures the probability that an obligor, that has paid his/her credit until time t, runs into arrears not later that time t+b. This ... -
Burned area prediction with semiparametric models
(CSIRO Publishing, 2016-04-27)[Abstract] Wildfires are one of the main causes of forest destruction, especially in Galicia (north-west Spain), where the area burned by forest fires in spring and summer is quite high. This work uses two semiparametric ... -
Empirical best prediction under area-level Poisson mixed models
(Springer, 2015-12-19)[Abstract] The paper studies the applicability of area-level Poisson mixed models to estimate small area counting indicators. Among the available procedures for fitting generalized linear models, the method of moments (MM) ... -
Goodness-of-fit tests for multiple regression with circular response
(2022)[Abstract]: Testing procedures for assessing a parametric regression model with a circular response and an Rd-valued covariate are proposed and analysed in this work. The test statistics are based on a circular distance ... -
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 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 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 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 ... -
Poverty Mapping Under Area-Level Random Regression Coefficient Poisson Models
(Oxford University Press, 2023-11)[Abstract]: Under an area-level random regression coefficient Poisson model, this article derives small area predictors of counts and proportions and introduces bootstrap estimators of the mean squared errors (MSEs). The ... -
Prediction of forest fires occurrences with area-level Poisson mixed models
(Academic Press, 2015-05-01)[Abstract] The number of fires in forest areas of Galicia (north-west of Spain) during the summer period is quite high. Local authorities are interested in analyzing the factors that explain this phenomenon. Poisson ... -
Rejoinder on: Nonparametric estimation in mixture cure models with covariates
(Springer Nature, 2023-06)[Abstract]: We thank all discussants for their insightful comments on our paper [López-Cheda, A., Peng, Y. & Jácome, M.A. Nonparametric estimation in mixture cure models with covariates. TEST 32, 467–495 (2023). ... -
Selection model for domains across time: application to labour force survey by economic activities
(Springer Nature, 2021-03)[Abstract]: This paper introduces a small area estimation approach that borrows strength across domains (areas) and time and is efficiently used to obtain labour force estimators by economic activity. Specifically, the ... -
Small area estimation of average compositions under multivariate nested error regression models
(Springer Science and Business Media Deutschland GmbH, 2023)[Abstract]: This paper investigates the small area estimation of population averages of unit-level compositional data. The new methodology transforms the compositions into vectors of Rm and assumes that the vectors follow ... -
Small area estimation of labour force indicators under a multinomial model with correlated time and area effects
(Wiley-Blackwell Publishing Ltd., 2014-09-30)[Abstract] The aim of the paper is the estimation of small area labour force indicators like totals of employed and unemployed people and unemployment rates. Small area estimators of these quantities are derived from four ... -
Small area estimation of proportions under area-level compositional mixed models
(Springer Nature, 2020-09)[Abstract]: This paper introduces area-level compositional mixed models by applying transformations to a multivariate Fay–Herriot model. Small area estimators of the proportions of the categories of a classification variable ... -
Small area prediction of proportions and counts under a spatial Poisson mixed model
(Springer Nature, 2023-10-31)[Abstract]: This paper introduces an area-level Poisson mixed model with SAR(1) spatially correlated random effects. Small area predictors of proportions and counts are derived from the new model and the corresponding mean ...
