Search results for "bayesian"
showing 10 items of 604 documents
IceCube search for neutrinos coincident with compact binary mergers from LIGO-Virgo's first gravitational-wave transient catalog
2020
Using the IceCube Neutrino Observatory, we search for high-energy neutrino emission coincident with compact binary mergers observed by the LIGO and Virgo gravitational-wave (GW) detectors during their first and second observing runs. We present results from two searches targeting emission coincident with the sky localization of each GW event within a 1000 s time window centered around the reported merger time. One search uses a model-independent unbinned maximum-likelihood analysis, which uses neutrino data from IceCube to search for pointlike neutrino sources consistent with the sky localization of GW events. The other uses the Low-Latency Algorithm for Multi-messenger Astrophysics, which …
Multioutput Automatic Emulator for Radiative Transfer Models
2018
This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…
GIGJ: a crustal gravity model of the Guangdong Province for predicting the geoneutrino signal at the JUNO experiment
2019
Gravimetric methods are expected to play a decisive role in geophysical modeling of the regional crustal structure applied to geoneutrino studies. GIGJ (GOCE Inversion for Geoneutrinos at JUNO) is a 3D numerical model constituted by ~46 x 10$^{3}$ voxels of 50 x 50 x 0.1 km, built by inverting gravimetric data over the 6{\deg} x 4{\deg} area centered at the Jiangmen Underground Neutrino Observatory (JUNO) experiment, currently under construction in the Guangdong Province (China). The a-priori modeling is based on the adoption of deep seismic sounding profiles, receiver functions, teleseismic P-wave velocity models and Moho depth maps, according to their own accuracy and spatial resolution. …
Revisiting the Epipalaeolithic-Neolithic Transition in the Extreme NW of Africa : The Latest Results of the Chronological Sequence of the Cave of Kaf…
2021
[EN] This study focuses on the chronostratigraphic sequence of the Cave of Kaf Taht el-Ghar (Dar Ben Karrich, Tétouan, Morocco) excavated in 2012 in the framework of the AGRIWESTMED research project. The broad sequence reveals a series of occupations ranging from the Pleistocene (Moroccan Aterian) to recent historical times. Our research identifies a rich Early Neolithic phase (sixth millennium cal BC) containing the earliest pottery and domesticated animal and plant remains in the western Maghreb. However, this Early Neolithic level is not an immediate successor of the last traces of the Epipalaeolithic hunter-gatherer occupation, which started at the end of the Younger Dryas (10,900–9700 …
Using latent variable models to identify large networks of species‐to‐species associations at different spatial scales
2015
Summary We present a hierarchical latent variable model that partitions variation in species occurrences and co-occurrences simultaneously at multiple spatial scales. We illustrate how the parameterized model can be used to predict the occurrences of a species by using as predictors not only the environmental covariates, but also the occurrences of all other species, at all spatial scales. We leverage recent progress in Bayesian latent variable models to implement a computationally effective algorithm that enables one to consider large communities and extensive sampling schemes. We exemplify the framework with a community of 98 fungal species sampled in c. 22 500 dead wood units in 230 plot…
A hierarchical Bayesian Beta regression approach to study the effects of geographical genetic structure and spatial autocorrelation on species distri…
2019
Global climate change (GCC) may be causing distribution range shifts in many organisms worldwide. Multiple efforts are currently focused on the development of models to better predict distribution range shifts due to GCC. We addressed this issue by including intraspecific genetic structure and spatial autocorrelation (SAC) of data in distribution range models. Both factors reflect the joint effect of ecoevolutionary processes on the geographical heterogeneity of populations. We used a collection of 301 georeferenced accessions of the annual plant Arabidopsis thaliana in its Iberian Peninsula range, where the species shows strong geographical genetic structure. We developed spatial and nonsp…
Neogene paleogeography provides context for understanding the origin and spatial distribution of cryptic diversity in a widespread Balkan freshwater …
2017
BackgroundThe Balkans are a major biodiversity and endemism hotspot, worldwide. Among the freshwater biota, amphipods are known for their high cryptic diversity. However, little is known about the temporal and paleogeographic aspects of their evolutionary history. We used paleogeography as a framework for understanding the onset of diversification inGammarus roeselii: (1) we hypothesised that, given the high number of isolated waterbodies in the Balkans, the species is characterised by high level of cryptic diversity, even on a local scale; (2) the long geological history of the region might promote pre-Pleistocene divergence between lineages; (3) given thatG. roeseliithrives both in lakes …
Traits mediate niches and co‐occurrences of forest beetles in ways that differ among bioclimatic regions
2021
Aim The aim of this study was to investigate the role of traits in beetle community assembly and test for consistency in these effects among several bioclimatic regions. We asked (1) whether traits predicted species’ responses to environmental gradients (i.e. their niches), (2) whether these same traits could predict co-occurrence patterns and (3) how consistent were niches and the role of traits among study regions. Location Boreal forests in Norway and Finland, temperate forests in Germany. Taxon Wood-living (saproxylic) beetles. Methods We compiled capture records of 468 wood-living beetle species from the three regions, along with nine morphological and ecological species traits. Eight …
The Bias of combining variables on fish's aggressive behavior studies.
2019
Made available in DSpace on 2019-10-06T16:27:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-01 Quantifying animal aggressive behavior by behavioral units, either displays or attacks, is a common practice in animal behavior studies. However, this practice can generate a bias in data analysis, especially when the variables have different temporal patterns. This study aims to use Bayesian Hierarchical Linear Models (B-HLMs) to analyze the feasibility of pooling the aggressive behavior variables of four cichlids species. Additionally, this paper discusses the feasibility of combining variables by examining the usage of different sample sizes and family distributions to aggressive …
Seasonality of spatial patterns of abundance, biomass and biodiversity in a demersal community of the NW Mediterranean Sea
2020
14 pages, 5 figures, 4 tables