A network Poisson model for weighted directed networks with covariates

Abstract We estimate a travel cost model for the George Washington & Jefferson National Forests using an On-Site Latent Class Poisson Model. We show that the constraints of ad-hoc truncation and homogenous preferences significantly impact consumer surplus estimates derived from the on-site travel cost model. By relaxing the constraints, we show that more than one class of visitors with unique preferences exists in the population. The resulting demand functions, price responsive behaviors, and consumer surplus estimates reflect differences across these classes of visitors. With heterogeneous preferences, a group of ‘local residents’ exists with a probability of 8% and, on average take 113 visits.

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An Efficient Algorithm to Determine the Connectivity of Complex Directed Networks

IEEE Transactions on Cybernetics ◽

10.1109/tcyb.2020.3035034 ◽

2020 ◽

pp. 1-8

Author(s):

Zhuo Wang ◽

Yuanqing Wu ◽

Yong Xu ◽

Renquan Lu

Keyword(s):

Efficient Algorithm ◽

Directed Networks

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Distributed support vector machines over dynamic balanced directed networks

IEEE Control Systems Letters ◽

10.1109/lcsys.2021.3086388 ◽

2021 ◽

pp. 1-1

Author(s):

Mohammadreza Doostmohammadian ◽

Alireza Aghasi ◽

Themistoklis Charalambous ◽

Usman A. Khan

Keyword(s):

Support Vector Machines ◽

Support Vector ◽

Directed Networks ◽

Vector Machines

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Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates

Mathematics ◽

10.3390/math9030282 ◽

2021 ◽

Vol 9 (3) ◽

pp. 282

Author(s):

Mabel Morales-Otero ◽

Vicente Núñez-Antón

Keyword(s):

Infant Mortality ◽

Count Data ◽

Spatial Dependence ◽

Poisson Model ◽

Mortality Rates ◽

Estimation Methods ◽

Neighborhood Structure ◽

Specific Context ◽

Count Data Models ◽

Conditional Mean

In this paper, we review overdispersed Bayesian generalized spatial conditional count data models. Their usefulness is illustrated with their application to infant mortality rates from Colombian regions and by comparing them with the widely used Besag–York–Mollié (BYM) models. These overdispersed models assume that excess of dispersion in the data may be partially caused from the possible spatial dependence existing among the different spatial units. Thus, specific regression structures are then proposed both for the conditional mean and for the dispersion parameter in the models, including covariates, as well as an assumed spatial neighborhood structure. We focus on the case of response variables following a Poisson distribution, specifically concentrating on the spatial generalized conditional normal overdispersion Poisson model. Models were fitted by making use of the Markov Chain Monte Carlo (MCMC) and Integrated Nested Laplace Approximation (INLA) algorithms in the specific context of Bayesian estimation methods.

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Distributed Asymptotic Consensus in Directed Networks of Nonaffine Systems With Nonvanishing Disturbance

IEEE/CAA Journal of Automatica Sinica ◽

10.1109/jas.2021.1004021 ◽

2021 ◽

Vol 8 (6) ◽

pp. 1133-1140

Author(s):

Qingling Wang ◽

Changyin Sun

Keyword(s):

Directed Networks

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Intra-urban differentials of congenital and acquired syphilis and syphilis in pregnant women in an urban area in northeastern Brazil

Transactions of the Royal Society of Tropical Medicine and Hygiene ◽

10.1093/trstmh/trab011 ◽

2021 ◽

Author(s):

Talita Araujo de Souza ◽

Karen Kaline Teixeira ◽

Reginaldo Lopes Santana ◽

Cinthia Barros Penha ◽

Arthur de Almeida Medeiros ◽

...

Keyword(s):

Relative Risk ◽

Pregnant Women ◽

Congenital Syphilis ◽

Kernel Density ◽

Poisson Model ◽

Northeastern Brazil ◽

Smoothing Function ◽

Density Estimator ◽

Epidemic Disease ◽

Peripheral Areas

Abstract Background Currently syphilis is considered an epidemic disease worldwide. The objective of this study was to identify intra-urban differentials in the occurrence of congenital and acquired syphilis and syphilis in pregnant women in the city of Natal, in northeast Brazil. Methods Cases of syphilis recorded by the municipal surveillance system from 1 January 2011 to 30 December 2018 were analysed. Spatial statistical analyses were performed using the kernel density estimator of the quadratic smoothing function (weighted). SaTScan software was applied for the calculation of risk based on a discrete Poisson model. Results There were 2163 cases of acquired syphilis, 738 cases of syphilis in pregnant women and 1279 cases of congenital syphilis. Kernel density maps showed that the occurrence of cases is more prevalent in peripheral areas and in areas with more precarious urban infrastructure. In 2011–2014 and 2015–2018, seven statistically significant clusters of acquired syphilis were identified. From 2011 to 2014, the most likely cluster had a relative risk of 3.54 (log likelihood ratio [LLR] 38 895; p<0.001) and from 2015 to 2018 the relative risk was 0.54 (LLR 69 955; p<0.001). Conclusions In the municipality of Natal, there was a clustered pattern of spatial distribution of syphilis, with some areas presenting greater risk for the occurrence of new cases.

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