Listar GI-MODES - Artigos por título
Mostrando ítems 79-98 de 122
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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 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 ... -
Nonparametric multiple regression estimation for circular response
(2021)Nonparametric estimators of a regression function with circular response and -valued predictor are considered in this work. Local polynomial estimators are proposed and studied. Expressions for the asymptotic conditional ... -
npcure: An R Package for Nonparametric Inference in Mixture Cure Models
(Technische Universitaet Wien, 2021)[Abstract] Mixture cure models have been widely used to analyze survival data with a cure fraction. They assume that a subgroup of the individuals under study will never experience the event (cured subjects). So, the goal ... -
Of Fears and Budgets: Strategies of Control in Vespa velutina Invasion and Lessons for Best Management Practices
(Springer, 2022)[Abstrat] Implementing management practices for the control of invasive species can be a complex task with multiple dimensions, where the identification of stakeholders and drivers of those practices is of paramount ... -
On egalitarian values for cooperative games with a priori unions
(Springer & Spanish Society of Statistics and Operations Research, 2020)[Abstract]: In this paper, we extend the equal division and the equal surplus division values for transferable utility cooperative games to the more general setup of transferable utility cooperative games with a priori ... -
On egalitarian values for cooperative games with level structures
(Springer Science and Business Media Deutschland GmbH, 2023)[Abstract]: In this paper we extend the equal division and the equal surplus division values for transferable utility cooperative games to the more general setup of transferable utility cooperative games with level structures. ... -
On the Reliability of Machine Learning Models for Survival Analysis When Cure Is a Possibility
(MDPI, 2023-10-02)[Abstract]: In classical survival analysis, it is assumed that all the individuals will experience the event of interest. However, if there is a proportion of subjects who will never experience the event, then a standard ... -
On the uniform strong consistency of local polynomial regression under dependence conditions
(Taylor & Francis, 2003)[Abstract] In this paper, nonparametric estimators of the regression function, and its derivatives, obtained by means of weighted local polynomial fitting are studied. Consider the fixed regression model where the error ... -
Ordinal Time Series Analysis with the R Package otsfeatures
(MDPI, 2023-06)[Abstract] The 21st century has witnessed a growing interest in the analysis of time series data. While most of the literature on the topic deals with real-valued time series, ordinal time series have typically received ... -
Outlier Detection for Multivariate Time Series: A Functional Data Approach ®
(Elsevier, 2021)[Abstract] A method for detecting outlier samples in a multivariate time series dataset is proposed. It is assumed that an outlying series is characterized by having been generated from a different process than those ... -
Poisson mixed models for predicting number of fires
(CSIRO, 2019-03)[Abstract]: Wildfires are considered one of the main causes of forest destruction. In recent years, the number of forest fires and burned area in Mediterranean regions have increased. This problem particularly affects ... -
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 ... -
Predicting rainfall and irrigation requirements of corn in Ecuador
(Elsevier Ltd, 2023-08)[Abstract]: This work is a case study whose objective is prediction of irrigation needs of corn crops in different regions of Ecuador; being this a fundamental basic food for the country's economy, as in the remaining ... -
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 ... -
Probability of default estimation in credit risk using mixture cure models
(Elsevier, 2024-01)[Abstract]: An estimator of the probability of default (PD) in credit risk is proposed. It is derived from a nonparametric conditional survival function estimator based on cure models. Asymptotic expressions for the bias ... -
ProjectManagement: an R Package for Managing Projects
(R Foundation for Statistical Computing, 2020)[Abstract]:Project management is an important body of knowledge and practices that comprises the planning, organisation and control of resources to achieve one or more pre-determined objectives. In this paper, we introduce ... -
Quantile Cross-Spectral Density: A Novel and Effective Tool for Clustering Multivariate Time Series
(Elsevier, 2021)[Abstract] Clustering of multivariate time series is a central problem in data mining with applications in many fields. Frequently, the clustering target is to identify groups of series generated by the same multivariate ... -
Quantile-based fuzzy C-means clustering of multivariate time series: Robust techniques
(Elsevier, 2022-11)[Abstract]: Robust fuzzy clustering of multivariate time series is addressed when the clustering purpose is grouping together series generated from similar stochastic processes. Robustness to the presence of anomalous ...
