This paper addresses parameter estimation for an optical transient signal when the received data has been right-censored. We develop an expectation-maximization (EM) algorithm to estimate the amplitude of a Poisson intensity with a known shape in the presence of additive background counts, where the measurements are subject to saturation effects. We compare the results of our algorithm with those of an EM algorithm that is unaware of the censoring.
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http://dx.doi.org/10.1364/JOSAA.35.001228 | DOI Listing |
PNAS Nexus
January 2025
Department of Mathematics, Aston University, Birmingham B4 7ET, United Kingdom.
Understanding the relation between cortical neuronal network structure and neuronal activity is a fundamental unresolved question in neuroscience, with implications to our understanding of the mechanism by which neuronal networks evolve over time, spontaneously or under stimulation. It requires a method for inferring the structure and composition of a network from neuronal activities. Tracking the evolution of networks and their changing functionality will provide invaluable insight into the occurrence of plasticity and the underlying learning process.
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August 2024
Department of Mathematics, University of Texas at Arlington, Texas, USA 76019.
Cure rate models have been thoroughly investigated across various domains, encompassing medicine, reliability, and finance. The merging of machine learning (ML) with cure models is emerging as a promising strategy to improve predictive accuracy and gain profound insights into the underlying mechanisms influencing the probability of cure. The current body of literature has explored the benefits of incorporating a single ML algorithm with cure models.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Statistics, Western Michigan University, Kalamazoo, MI, United States of America.
Graphical models have been widely used to explicitly capture the statistical relationships among the variables of interest in the form of a graph. The central question in these models is to infer significant conditional dependencies or independencies from high-dimensional data. In the current literature, it is common to assume that the high-dimensional data come from a homogeneous source and follow a parametric graphical model.
View Article and Find Full Text PDFFront Psychol
December 2024
Natural and Artificial Cognition Laboratory, Department of Humanistic Studies, University of Naples "Federico II", Naples, Italy.
Introduction: Missing data in psychometric research presents a substantial challenge, impacting the reliability and validity of study outcomes. Various factors contribute to this issue, including participant non-response, dropout, or technical errors during data collection. Traditional methods like mean imputation or regression, commonly used to handle missing data, rely upon assumptions that may not hold on psychological data and can lead to distorted results.
View Article and Find Full Text PDFPLoS One
December 2024
São Paulo State University (Unesp), School of Sciences and Engineering, Tupã, São Paulo, Brasil.
Meteorological data acquired with precision, quality, and reliability are crucial in various agronomy fields, especially in studies related to reference evapotranspiration (ETo). ETo plays a fundamental role in the hydrological cycle, irrigation system planning and management, water demand modeling, water stress monitoring, water balance estimation, as well as in hydrological and environmental studies. However, temporal records often encounter issues such as missing measurements.
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