Listar GI-MODES - Artigos por título
Mostrando ítems 91-110 de 122
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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 ... -
Quantile-Based Fuzzy Clustering of Multivariate Time Series in the Frequency Domain
(Elsevier, 2022)[Abstract] A novel procedure to perform fuzzy clustering of multivariate time series generated from different dependence models is proposed. Different amounts of dissimilarity between the generating models or changes on ... -
Queues in Reliability
(Wiley, 2007)Queueing models can be useful in solving many complex reliability problems. Component failures are usually interpreted as the arrival of customers and the repair or replacement of failed components is typically associated ... -
Recursive local polynomial regression under dependence conditions
(Springer, 2000)In the case of the random design nonparametric regression, one recursive local polynomial smoother is considered. Expressions for the bias and the variance matrix of the estimators of the regression function and its ... -
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). ... -
Relationship of depression in participants with nonspecific acute or subacute low back pain and no-pain by age distribution
(Dove Press, 2017-01)[Abstract] Background and purpose: Nonspecific low back pain (LBP) is the most prevalent musculoskeletal condition in various age ranges and is associated with depression. The aim of this study was to determine the Beck ... -
River flow modelling using nonparametric functional data analysis
(John Wiley & Sons Ltd and The Chartered Institution of Water and Environmental Management (CIWEM), 2018)[Abstract]: Time series and extreme value analyses are two statistical approaches usually applied to study hydrological data. Classical techniques, such as autoregressive integrated moving-average models (in the case of ... -
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 ... -
Sharing delay costs in stochastic scheduling problems with delays
(Springer, 2020)[Abstract]: An important problem in project management is determining ways to distribute amongst activities the costs that are incurred when a project is delayed because some activities end later than expected. In this ... -
Simultaneous Inference for Empirical Best Predictors With a Poverty Study in Small Areas
(Taylor and Francis Group, 2023-01)[Abstract]: Today, generalized linear mixed models (GLMM) are broadly used in many fields. However, the development of tools for performing simultaneous inference has been largely neglected in this domain. A framework for ... -
Simultaneous inference for linear mixed model parameters with an application to small area estimation
(John Wiley & Sons, 2022)[Abstract]: Over the past decades, linear mixed models have attracted considerable attention in various fields of applied statistics. They are popular whenever clustered, hierarchical or longitudinal data are investigated. ... -
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 expenditure means and ratios under a unit-level bivariate linear mixed model
(Taylor and Francis Group, 2022)[Abstract]: Under a unit-level bivariate linear mixed model, this paper introduces small area predictors of expenditure means and ratios, and derives approximations and estimators of the corresponding mean squared errors. ...
