Search results for "Inference"

showing 10 items of 478 documents

Recent statistical advances and applications of species distribution modeling

2019

En el mundo en que vivimos, producimos aproximadamente 2.5 quintillones de bytes de datos por día. Esta enorme cantidad de datos proviene de las redes sociales, Internet, satélites, etc. Todos estos datos, que se pueden registrar en el tiempo o en el espacio, son información que puede ayudarnos a comprender la propagación de una enfermedad, el movimiento de especies o el cambio climático. El uso de modelos estadísticos complejos ha aumentado recientemente en el contexto del estudio de la distribución de especies. Esta complejidad ha hecho que los procesos inferenciales y predictivos sean difíciles de realizar. El enfoque bayesiano se ha convertido en una buena opción para lidiar con estos m…

inlabayesian inferencegeostatistics:MATEMÁTICAS::Estadística [UNESCO]species distribution models:CIENCIAS DE LA VIDA::Biometría [UNESCO]UNESCO::CIENCIAS DE LA VIDA::BiometríaUNESCO::MATEMÁTICAS::Estadística
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Genomic divergence landscape in recurrently hybridizing Chironomus sister taxa suggests stable steady state between mutual gene flow and isolation

2021

Abstract Divergence is mostly viewed as a progressive process often initiated by selection targeting individual loci, ultimately resulting in ever increasing genomic isolation due to linkage. However, recent studies show that this process may stall at intermediate stable equilibrium states without achieving complete genomic isolation. We tested the extent of genomic isolation between two recurrently hybridizing nonbiting midge sister taxa, Chironomus riparius and Chironomus piger, by analyzing the divergence landscape. Using a principal component‐based method, we estimated that only about 28.44% of the genomes were mutually isolated, whereas the rest was still exchanged. The divergence land…

islands of divergencebiologyreproductive isolationlcsh:EvolutionIntrogressionReproductive isolationbiology.organism_classificationGene flowDivergenceNegative selectionddc:580ddc:590Sister groupEffective population sizespeciationEvolutionary biologyddc:570Geneticslcsh:QH359-425ChironomusEcology Evolution Behavior and SystematicsAdmixture inferenceEvolution Letters
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Meeting the Challenges of High-Dimensional Single-Cell Data Analysis in Immunology

2019

Recent advances in cytometry have radically altered the fate of single-cell proteomics by allowing a more accurate understanding of complex biological systems. Mass cytometry (CyTOF) provides simultaneous single-cell measurements that are crucial to understand cellular heterogeneity and identify novel cellular subsets. High-dimensional CyTOF data were traditionally analyzed by gating on bivariate dot plots, which are not only laborious given the quadratic increase of complexity with dimension but are also biased through manual gating. This review aims to discuss the impact of new analysis techniques for in-depths insights into the dynamics of immune regulation obtained from static snapshot …

lcsh:Immunologic diseases. Allergysingle-cell genomicssingle-cell profilinghigh-dimensional data analysisCyTOFtrajectory inferencelcsh:RC581-607visualizationFrontiers in Immunology
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Diachrony and Neology: Semantic Change, Subjectivization and the Representation of Thinking. The Meaning of the Catalan Verb Esmar, from ‘Setting the…

2015

L’estudi de la neologia és indestriable de l’estudi del canvi lingüístic i, doncs, de la diacronia. Ens proposem ací descriure el procés de canvi semàntic que va experimentar el verb esmar, forma patrimonial del llatí *adaestimare, paral·lela del cultisme estimar. Aquesta recerca es fonamenta en l’aprofitament dels corpus textuals i altres materials despullats manualment. Sobre aquests materials, s’ha assajat l’anàlisi de la subjectivació i de les inferències que proposa la teoria de la inferència invitada del canvi semàntic (= TIICS). The study of neology is inextricably linked with the study of language change and, therefore, with diachrony. The aim of this paper is to describe the semant…

lcsh:Language and LiteratureLinguistics and LanguagepragmàticaSubjectivacióFilologíasEvidentialityLanguage and LinguisticsPragmàticalcsh:P1-1091InferenceSemàntica diacrònicaFilología Catalanaevidencialitatsemàntica diacrònica; inferència; subjectivació; evidencialitat; pragmàtica; canvi semànticCanvi semànticUNESCO::CIENCIAS DE LAS ARTES Y LAS LETRASinferènciaLingüísticaDiachronic semanticsPragmaticsPhilosophycanvi semànticlcsh:Philology. LinguisticsSubjectivizationInferènciaEvidencialitat:CIENCIAS DE LAS ARTES Y LAS LETRAS [UNESCO]semàntica diacrònicalcsh:PsubjectivacióHumanitiesSemantic change
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3 ′-5 ′ crosstalk contributes to transcriptional bursting

2019

Abstract Background Transcription in mammalian cells is a complex stochastic process involving shuttling of polymerase between genes and phase-separated liquid condensates. It occurs in bursts, which results in vastly different numbers of an mRNA species in isogenic cell populations. Several factors contributing to transcriptional bursting have been identified, usually classified as intrinsic, in other words local to single genes, or extrinsic, relating to the macroscopic state of the cell. However, some possible contributors have not been explored yet. Here, we focus on processes at the 3 ′ and 5 ′ ends of a gene that enable reinitiation of transcription upon termination. Results Using Bay…

lcsh:QH426-470TransgeneParameter inference03 medical and health sciences0302 clinical medicineTranscription (biology)Gene expressionmedicineCompartment (development)QAlcsh:QH301-705.5GenePolymerase030304 developmental biologyTranscriptional burstingMessenger RNA0303 health sciencesMathematical modellingbiologyQHCell cyclemedicine.diseaseCell biologyLiquid-liquid phase separationlcsh:GeneticsCrosstalk (biology)lcsh:Biology (General)Biological noisebiology.proteinGene expressionGene looping030217 neurology & neurosurgeryTranscriptional noiseGenome Biology
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Book Review: Statistical Inference as Severe Testing

2019

logicphilosophybusiness.industrylcsh:BF1-990epistemologymethodologycomputer.software_genreBook Reviewlcsh:PsychologystatisticsStatistical inferencePsychologyArtificial intelligencebusinessPsychologycomputerGeneral PsychologyNatural language processingFrontiers in Psychology
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Estimating the Bayesian posterior distribution of indirect effects in causal longitudinal mediation analysis

Many research studies aim to unveil the causal mechanism underlying a particular phenomenon; mediation analysis is increasingly used for this scope, and longitudinal data are particularly suited for mediation since they ensure the correct temporal order among variables and the time spanning allows the causal effects to unfold. This explains the rise of interest in the topic of longitudinal mediation analysis. Many approaches have been proposed to cope with longitudinal mediation (Fosen et al., 2005; Lin et al., 2017), among which mixed-effect modelling. In a recent paper, Bind et al. (Biostatistics, 2016) made use of generalised mixed effect models and provided conditions for the identifiab…

longitudinal dataMediation analysiBayesian inferencemixed-effect modelsSettore SECS-S/01 - Statistica
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Bayesian causal mediation analysis through linear mixed-effect models

2022

In mediational settings, the main focus is on the estimation of the indirect effect of an exposure on an outcome through a third variable called mediator. The traditional maximum likelihood estimation method presents several problems in the estimation of the standard error and the confidence interval of the indirect effect. In this paper, we propose a Bayesian approach to obtain the posterior distribution of the indirect effect through MCMC, in the context of mediational mixed models for longitudinal data. A simulation study shows that our method outperforms the traditional maximum likelihood approach in terms of bias and coverage rates.

longitudinal mediation analysis mixed effect models Bayesian methods causal inferenceSettore SECS-S/01 - Statistica
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Computational complexity of prediction strategies

1977

The value f(m+1) is predicted from given f(1), ..., f(m). For every enumeration T(n, x) there is a strategy that predicts the n-th function of T making no more than log2(n) errors (Barzdins-Freivalds). It is proved in the paper that such "optimal" strategies require 2^2^cm time to compute the m-th prediction (^ stands for expoentiation).

machine learning:MATHEMATICS [Research Subject Categories]function predictioninductive inference
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Towards a theory of inductive inference

1973

machine learninginductive inference
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