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1. A variable selection package driving Netica with Python

Author:
Beuzen, Tomas; Simmons, Joshua
Source:
Environmental modelling & software 2019 v.115 pp. 1-5
ISSN:
1364-8152
Subject:
Bayesian theory,   etc   ; artificial intelligence; computer software; models;     Show all 4 Subjects
Abstract:
... Bayesian Networks (BNs) are useful methods of probabilistically modelling environmental systems. BN performance is sensitive to the number of variables included in the model framework. The selection of the optimum set of variables to include in a BN (“variable selection”) is therefore a key part of the BN modelling process. While variable selection is an issue dealt with in the wider BN and machin ...
DOI:
10.1016/j.envsoft.2019.01.018

2. Skeletal age-at-death estimation: Bayesian versus regression methods

Author:
Nikita, Efthymia; Nikitas, Panos
Source:
Forensic science international 2019
ISSN:
0379-0738
Subject:
Bayesian theory,   etc   ; linear models; prediction; regression analysis;     Show all 4 Subjects
Abstract:
... Age-at-death estimation in a skeletal assemblage (target sample) is biased by the demographic profile of the material used for age prediction (training sample) when this profile is different from that of the target sample. This bias is minimized if the demographic profile of the target sample is properly taken into account in the method developed for age-at-death estimation. In the Bayesian approa ...
DOI:
10.1016/j.forsciint.2019.01.033

3. Covariate selection with group lasso and doubly robust estimation of causal effects

Author:
Koch, Brandon; Vock, David M.; Wolfson, Julian
Source:
Biometrics 2018 v.74 no.1 pp. 8-17
ISSN:
0006-341X
Subject:
Bayesian theory,   etc   ; biometry; models;     Show all 3 Subjects
Abstract:
... The efficiency of doubly robust estimators of the average causal effect (ACE) of a treatment can be improved by including in the treatment and outcome models only those covariates which are related to both treatment and outcome (i.e., confounders) or related only to the outcome. However, it is often challenging to identify such covariates among the large number that may be measured in a given stud ...
DOI:
10.1111/biom.12736

4. Multilook SAR intensity image segmentation based on Voronoi tessellation and a Gamma mixture model

Author:
Li, Xiaoli; Zhao, Quanhua; Li, Yu
Source:
Remote sensing letters 2019 v.10 no.3 pp. 254-263
ISSN:
2150-7058
Subject:
Bayesian theory,   etc   ; Markov chain; algorithms; models; remote sensing;     Show all 5 Subjects
Abstract:
... This letter presents an SAR intensity image segmentation algorithm by combining Voronoi tessellation and Gamma Mixture Model (GaMM). By Voronoi tessellation, the domain of the image is partitioned into a collection of sub-regions, which acts on region based segmentation to overcome speckle noise. GaMMs defined on the sub-regions can be used to model the complicate distributions of the homogeneous ...
DOI:
10.1080/2150704X.2018.1547446

5. Using Bayesian change point model to enhance understanding of the shifting nutrients-phytoplankton relationship

Author:
Liang, Zhongyao; Qian, Song S.; Wu, Sifeng; Chen, Huili; Liu, Yong; Yu, Yanhong; Yi, Xuan
Source:
Ecological modelling 2019 v.393 pp. 120-126
ISSN:
0304-3800
Subject:
Bayesian theory,   etc   ; ecosystems; lakes; models; nutrients; total nitrogen; total phosphorus;     Show all 7 Subjects
Abstract:
... Possibility of shifting nutrients-phytoplankton relationship in lakes requires methods with the ability to testify abrupt relationship change to facilitate efficient management. Bayesian change point model (BCPM) can handle multiple shifts in coefficients and/or in residual errors and therefore suits this requirement. We employed BCPMs to enhance understanding of the shifting nutrients-Chlorophyll ...
DOI:
10.1016/j.ecolmodel.2018.12.008

6. Bayesian updating to estimate extinction from sequential observation data

Author:
Thompson, Colin J.; Kodikara, Saritha; Burgman, Mark A.; Demirhan, Haydar; Stone, Lewi
Source:
Biological conservation 2019 v.229 pp. 26-29
ISSN:
0006-3207
Subject:
Bayesian theory,   etc   ; data collection; extinction; natural resources conservation; probability; surveys;     Show all 6 Subjects
Abstract:
... Several new approaches to estimating the probability that a species is extinct have emerged recently. Different foundational assumptions can lead to different interpretations of data and potentially to different conclusions. To explore the implications of alternative formulations, here we develop and illustrate a Bayesian Updating method for inferring extinction based on records of observations an ...
DOI:
10.1016/j.biocon.2018.11.003

7. Correction to: Monogenean parasites infect ornamental fish imported to Australia

Author:
Trujillo-González, A.; Becker, J. A.; Vaughan, D. B.; Hutson, K. S.
Source:
Parasitology research 2019 v.118 no.1 pp. 383-384
ISSN:
0932-0113
Subject:
Bayesian theory,   etc   ; Monogenea; ornamental fish; parasites; parasitology; phylogeny; Australia;     Show all 7 Subjects
Abstract:
... The phylogenetic tree (Figure 7) in the published document has incorrect Bayesian analysis posterior probabilities. This error prevents accurate analysis by future research in parasitology. The figure is therefore replaced by the corrected figure below. ...
DOI:
10.1007/s00436-018-6156-4

8. Mitochondrial genome of Paruterina candelabraria (Cestoda: Paruterinidae), with implications for the relationships between the genera Cladotaenia and Paruterina

Author:
Guo, Aijiang; Wang, Li; Zhang, Shaohua; Zheng, Yadong; Georgiev, Boyko B.; Luo, Xuenong; Huang, Siyang; Cai, Xuepeng
Source:
Acta tropica 2019 v.189 pp. 1-5
ISSN:
0001-706X
Subject:
Bayesian theory,   etc   ; Taeniidae; genes; mitochondria; mitochondrial genome; nucleotide sequences; phylogeny;     Show all 7 Subjects
Abstract:
... The taxonomic concept for the family Paruterinidae is controversial, especially concerning the position of the genus Cladotaenia, since the latter genus has been placed sometimes in other families, i.e. in the Taeniidae or in the distinct family Cladotaeniidae; finding a solution based on morphological data is difficult and molecular data on paruterinids and related groups are scarce. In this stud ...
DOI:
10.1016/j.actatropica.2018.09.016

9. Short-term air temperature forecasting using Nonparametric Functional Data Analysis and SARMA models

Author:
Curceac, Stelian; Ternynck, Camille; Ouarda, Taha B.M.J.; Chebana, Fateh; Niang, Sophie Dabo
Source:
Environmental modelling & software 2019 v.111 pp. 394-408
ISSN:
1364-8152
Subject:
Bayesian theory,   etc   ; air temperature; economic sectors; regression analysis;     Show all 4 Subjects
Abstract:
... Air temperature is a significant meteorological variable that affects social activities and economic sectors. In this paper, a non-parametric and a parametric approach are used to forecast hourly air temperature up to 24 h in advance. The former is a regression model in the Functional Data Analysis framework. The nonlinear regression operator is estimated using a kernel function. The smoothing par ...
DOI:
10.1016/j.envsoft.2018.09.017

10. Statistical consistency and phylogenetic inference: a brief review

Author:
Brower, Andrew V. Z.
Source:
Cladistics 2018 v.34 no.5 pp. 562-567
ISSN:
0748-3007
Subject:
Bayesian theory,   etc   ; phylogeny; statistical analysis;     Show all 3 Subjects
Abstract:
... The claim that parsimony can be statistically inconsistent remains the chief criticism of the cladistic approach, and also the main justification for alternative model‐based approaches such as maximum likelihood and Bayesian inference. Despite its refutation in the 1980s, this persistent myth of parsimony's Achilles’ heel is entrenched in the primary literature, and has metastasized into textbooks ...
DOI:
10.1111/cla.12216

11. A Bayesian nonparametric approach to causal inference on quantiles

Author:
Xu, Dandan; Daniels, Michael J.; Winterstein, Almut G.
Source:
Biometrics 2018 v.74 no.3 pp. 986-996
ISSN:
0006-341X
Subject:
Bayesian theory,   etc   ; biometry; kidneys; models;     Show all 4 Subjects
Abstract:
... We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given ...
DOI:
10.1111/biom.12863

12. Ex-situ priors: A Bayesian hierarchical framework for defining informative prior distributions in hydrogeology

Author:
Cucchi, Karina; Heße, Falk; Kawa, Nura; Wang, Changhong; Rubin, Yoram
Source:
Advances in water resources 2019 v.126 pp. 65-78
ISSN:
0309-1708
Subject:
Bayesian theory,   etc   ; algorithms; aquifers; case studies; data collection; models; probability distribution; stochastic processes;     Show all 8 Subjects
Abstract:
... Stochastic modeling is a common practice for modeling uncertainty in hydrogeology. In stochastic modeling, aquifer properties are characterized by their probability density functions (PDFs). The Bayesian approach for inverse modeling is often used to assimilate information from field measurements collected at a site into properties’ posterior PDFs. This necessitates the definition of a prior PDF, ...
DOI:
10.1016/j.advwatres.2019.02.003

13. Probabilistic programming: A review for environmental modellers

Author:
Krapu, Christopher; Borsuk, Mark
Source:
Environmental modelling & software 2019 v.114 pp. 40-48
ISSN:
1364-8152
Subject:
Bayesian theory,   etc   ; artificial intelligence; computer software; data collection; environmental models; prediction; statistical inference;     Show all 7 Subjects
Abstract:
... The development process for an environmental model involves multiple iterations of a planning-implementation-assessment cycle. Probabilistic programming languages (PPLs) are designed to expedite this process with general-purpose methods for implementing models, efficiently inferring their parameters, and generating probabilistic predictions. Probabilistic programming exists at the intersection of ...
DOI:
10.1016/j.envsoft.2019.01.014

14. The impacts of nonferrous metal price shocks on the macroeconomy in China from the perspective of resource security

Author:
Song, Wanting; Huang, Jianbai; Zhong, Meirui; Wen, Fenghua
Source:
Journal of cleaner production 2019 v.213 pp. 688-699
ISSN:
0959-6526
Subject:
Bayesian theory,   etc   ; decision making; inflation; issues and policy; labor; macroeconomics; metals; models; prices; China;     Show all 10 Subjects
Abstract:
... In recent years, the price of international nonferrous metals has undergone drastic fluctuations, which could exert significant shock effects on macroeconomic variables. Based on the perspective of resource security, this paper reveals the relationship between the nonferrous metal price shocks and China's macroeconomic variables by establishing a Dynamic Stochastic General Equilibrium (DSGE) model ...
DOI:
10.1016/j.jclepro.2018.12.037

15. A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with Bayesian optimization algorithm

Author:
He, Feifei; Zhou, Jianzhong; Feng, Zhong-kai; Liu, Guangbiao; Yang, Yuqi
Source:
Applied energy 2019 v.237 pp. 103-116
ISSN:
0306-2619
Subject:
Bayesian theory,   etc   ; algorithms; energy; lymphocytes; models; prediction; processing technology; regression analysis; temperature; China;     Show all 10 Subjects
Abstract:
... Short-term load forecasting plays an essential role in the safe and stable operation of power systems and has always been a vital research issue of energy management. In this research, a hybrid short-load forecasting method with Variational Mode Decomposition (VMD) and Long Short-Term Memory (LSTM) networks considering relevant factors which optimized by the Bayesian Optimization Algorithm (BOA) i ...
DOI:
10.1016/j.apenergy.2019.01.055

16. A study of background population of fibres on knife blades

Author:
Cammarota, Valentina; Schnegg, Michael; Massonnet, Geneviève
Source:
Forensic science international 2019 v.296 pp. 132-143
ISSN:
0379-0738
Subject:
Bayesian theory,   etc   ; blades; color; crime; fabrics; knives; lint cotton; microscopy; police; seizures;     Show all 10 Subjects
Abstract:
... Edged weapons are frequently used to commit violent crimes (e.g., homicides, assaults or sequestrations). Following a stabbing, a fibre transfer might occur from the damaged fabric to the blade. It is crucial to investigate whether the target fibres were transferred to the blade as a result of the stabbing and if they are in association with the offence or whether they originate from another unrel ...
DOI:
10.1016/j.forsciint.2019.01.006

17. Combining N2:Ar and Bayesian Methods to Quantify Underestimation and Uncertainty of Sediment Denitrification Determined by the Acetylene Inhibition Method

Author:
She, Dongli; Sun, Xiaoqin; Xia, Yongqiu
Source:
Water, air, and soil pollution 2019 v.230 no.3 pp. 52
ISSN:
0049-6979
Subject:
Bayesian theory,   etc   ; Markov chain; algorithms; denitrification; ecosystems; mass spectrometry; nitrification; nitrogen; nitrous oxide; sediments; soil; uncertainty;     Show all 12 Subjects
Abstract:
... Accurately determining denitrification rates is essential for estimating the nitrogen budget in flooded ecosystems. The acetylene inhibition method (AIT) is a simple and common technique for measuring sediment denitrification. However, incomplete inhibition of nitrous oxide reduction or concurrent inhibition of nitrification may lead to underestimations of denitrification rates, whereas the N₂:Ar ...
DOI:
10.1007/s11270-019-4100-6

18. Robust functional regression for wind speed forecasting based on Sparse Bayesian learning

Author:
Wang, Yun; Wang, Haibo; Srinivasan, Dipti; Hu, Qinghua
Source:
Renewable energy 2019 v.132 pp. 43-60
ISSN:
0960-1481
Subject:
Bayesian theory,   etc   ; electric power; models; regression analysis; renewable energy sources; wind speed;     Show all 6 Subjects
Abstract:
... Accurate wind speed forecasting is helpful for reducing the instantaneous fluctuation of voltage, and also has great practical significance on power dispatching and plan. There are two problems in wind speed forecasting: loss of details when transforming the high-resolution data into the low-resolution data and outliers existing in our data. So, a sparse Bayesian-based robust functional regression ...
DOI:
10.1016/j.renene.2018.07.083

19. Prediction uncertainty assessment of chromatography models using Bayesian inference

Author:
Briskot, Till; Stückler, Ferdinand; Wittkopp, Felix; Williams, Christopher; Yang, Jessica; Konrad, Susanne; Doninger, Katharina; Griesbach, Jan; Bennecke, Moritz; Hepbildikler, Stefan; Hubbuch, Jürgen
Source:
Journal of chromatography 2019 v.1587 pp. 101-110
ISSN:
0021-9673
Subject:
Bayesian theory,   etc   ; Markov chain; antibodies; cations; chromatography; decision making; mechanistic models; parameter uncertainty; pharmaceutical industry; prediction;     Show all 10 Subjects
Abstract:
... Mechanistic modeling of chromatography has been around in academia for decades and has gained increased support in pharmaceutical companies in recent years. Despite the large number of published successful applications, process development in the pharmaceutical industry today still does not fully benefit from a systematic mechanistic model-based approach. The hesitation on the part of industry to ...
DOI:
10.1016/j.chroma.2018.11.076

20. Bayesian updating for progressive excavation of high rock slopes using multi-type monitoring data

Author:
Sun, Yang; Huang, Jinsong; Jin, Wei; Sloan, Scott William; Jiang, Qinghui
Source:
Engineering geology 2019
ISSN:
0013-7952
Subject:
Bayesian theory,   etc   ; case studies; deformation; models; monitoring; parameter uncertainty; water power; China;     Show all 8 Subjects
Abstract:
... Systems for monitoring the deformation and stress conditions of excavated high rock slopes are usually implemented for safety reasons and to predict the stability of future works. This paper adopts Bayesian methods for updating important geomechanical parameters namely: E(III1), E(III2), E(IV2), E(f8), c(III1), c(III2), c(V1) and c(f8) in these types of cases. The proposed method utilizes parametr ...
DOI:
10.1016/j.enggeo.2019.02.013