Listar GI-MODES - Artigos por data de publicación
Mostrando ítems 41-60 de 123
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Distributed classification based on distances between probability distributions in feature space
(Elsevier, 2019-09)[Abstract]: We consider a distributed framework where training and test samples drawn from the same distribution are available, with the training instances spread across disjoint nodes. In this setting, a novel learning ... -
Analysis of interval‐grouped data in weed science: The binnednp Rcpp package
(John Wiley & Sons Ltd., 2019-09-13)[Abstract] Weed scientists are usually interested in the study of the distribution and density functions of the random variable that relates weed emergence with environmental indices like the hydrothermal time (HTT). ... -
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 ... -
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 ... -
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 ... -
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 ... -
Constructing a Control Chart Using Functional Data
(MDPI AG, 2020-01-02)[Abstract] This study proposes a control chart based on functional data to detect anomalies and estimate the normal output of industrial processes and services such as those related to the energy efficiency domain. Companies ... -
Inter-and Intra-Examiner Reliability of Supraspinatus Muscle Tendon Palpation: A Cross-Sectional Study by Ultrasonography
(Kauno Medicinos Universitetas,Kaunas University of Medicine, 2020-02-18)[Abstract] Background and objectives: Palpation is an inherent and basic skill of health professionals—particularly manual therapists who base their diagnosis and treatment in a clinical environment. Many authors have ... -
Altered pathways in methylome and transcriptome longitudinal analysis of normal weight and bariatric surgery women
(NLM (Medline), 2020-04-15)[Abstract] DNA methylation could provide a link between environmental, genetic factors and weight control and can modify gene expression pattern. This study aimed to identify genes, which are differentially expressed and ... -
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, ... -
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 ... -
How do early socioeconomic circumstances impact inflammatory trajectories? Findings from Generation XXI
(Elsevier, 2020-09)[Abstract]: Background: The association between socioeconomic position and markers of inflammation in adults, including C-reactive protein (CRP), is well-established. We hypothesized that children from families of ... -
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 ... -
Characterizing the Invasive Tumor Front of Aggressive Uterine Adenocarcinoma and Leiomyosarcoma
(Frontiers, 2021)[Abstract] The invasive tumor front (the tumor–host interface) is vitally important in malignant cell progression and metastasis. Tumor cell interactions with resident and infiltrating host cells and with the surrounding ... -
Epigenetic Landscape in Blood Leukocytes Following Ketosis and Weight Loss Induced by a Very Low Calorie Ketogenic Diet (VLCKD) in Patients With Obesity
(Elsevier, 2021)[Abstract] Background:The molecular mechanisms underlying the potential health benefits of a ketogenic diet areunknown and could be mediated by epigenetic mechanisms.Objective:To identify the changes in the obesity-related ... -
A distance correlation approach for optimum multiscale selection in 3D point cloud classification
(2021)[Abstract] Supervised classification of 3D point clouds using machine learning algorithms and handcrafted local features as covariates frequently depends on the size of the neighborhood (scale) around each point used to ... -
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 ... -
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 ... -
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 ... -
Statistical Quality Control with the qcr Package
(Technische Universitaet Wien, 2021)[Abstract] The R package qcr for Statistical Quality Control (SQC) is introduced and described. It includes a comprehensive set of univariate and multivariate SQC tools that completes and increases the SQC techniques ...
