Search results for "Bayesian model"

Vai strukturālās reformas spēs veicināt Latvijas ekonomisko izaugsmi: BMA un GMM novērtējumu liecības

2017

Pētījuma ietvaros tiek pielietota Beijesa modeļu svēršana (BMA) un vispārīgā momentu metode (GMM) Globālās Konkurētspējas apakšindeksu (GCI) datiem, lai identificētu strukturālo reformu jomas, kas var nozīmīgi paātrināt Latvijas ekonomisko izaugsmi. Novērtējumu rezultāti, kuros ņemta vērā gan modeļu nenoteiktība, gan endogenitāte liecina, ka ekonomisko izaugsmi var veicināt ar augstākām investīcijām, zemāku administratīvo slogu, stabilāku makroekonomisko vidi, paaugstinātu ārvalsts tiešo investīciju kvalitāti, kā arī ar attīstītākiem uzņēmējdarbības klasteriem. Ja šajās jomās Latvijas sniegums pēdējo 10 gadu laikā būtu trīs labāko Eiropas Savienības dalībvalstu līmenī, tad ienākumu līmenis …

Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015–2016

2019

We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015–December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases. Most of the dengue and Zika high-risk municipalities varied in their risk distributio…

SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations

2016

Various approaches to calling single-nucleotide variants (SNVs) or insertion-or-deletion (indel) mutations have been developed based on next-generation sequencing (NGS). However, most of them are dedicated to a particular type of mutation, e.g. germline SNVs in normal cells, somatic SNVs in cancer/tumor cells, or indels only. In the literature, efficient and integrated callers for both germline and somatic SNVs/indels have not yet been extensively investigated. We present SNVSniffer, an efficient and integrated caller identifying both germline and somatic SNVs/indels from NGS data. In this algorithm, we propose the use of Bayesian probabilistic models to identify SNVs and investigate a mult…

Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia

2018

The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015&ndash

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…

Integrating spatial management measures into fisheries: The Lepidorhombus spp. case study

2020

Most fisheries management systems rely on a set of regulatory measures to achieve desired objectives. Controls on catch and effort are usually supplemented with gear restrictions, minimum landing sizes, and in the framework of the new common fisheries policy, limitation of discards and by-catch. However, the increasing use of spatial management measures such as conservation areas or spatial and temporal area closures faces new challenges for fishery managers. Here we present an integrated spatial framework to identify areas in which undersized commercial species are more abundant. Once these areas are identified they could be avoided by fishers, minimizing the fishing impact over the immatu…

High‐resolution 3D forest structure explains ecomorphological trait variation in assemblages of saproxylic beetles

2022

1. Climate, topography and the 3D structure of forests are major drivers affecting local species communities. However, little is known about how the specific functional traits of saproxylic (wood-living) beetles, involved in the recycling of wood, might be affected by those environmental characteristics. 2. Here, we combine ecological and morphological traits available for saproxylic beetles and airborne laser scanning (ALS) data in Bayesian trait-based joint species distribution models to study how traits drive the distributions of more than 230 species in temperate forests of Europe. 3. We found that elevation (as a proxy for temperature and precipitation) and the proportion of conifers p…

Spatio-Temporal Assessment of the European Hake (Merluccius merluccius) Recruits in the Northern Iberian Peninsula

2021

14 pages, 9 figures, 3 tables.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)

Statistical models and inference for spatial point patterns with intensity-dependent marks

2009

Bayesian model averaging and weighted-average least squares: Equivariance, stability, and numerical issues

2011

In this article, we describe the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals, which implement, respectively, the exact Bayesian model-averaging estimator and the weighted-average least-squares estimator developed by Magnus, Powell, and Prüfer (2010, Journal of Econometrics 154: 139–153). Unlike standard pretest estimators that are based on some preliminary diagnostic test, these model-averaging estimators provide a coherent way of making inference on the regression parameters of interest by taking into account the uncertainty due to both the estimation and the model selection steps. Spec…