Efficient and flexible Integration of variant characteristics in rare variant association studies using integrated nested Laplace approximation. [PDF]
PLoS Computational Biology, 2021 Rare variants are thought to play an important role in the etiology of complex diseases and may explain a significant fraction of the missing heritability in genetic disease studies. Next-generation sequencing facilitates the association of rare variants
Hana Susak +9 more
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Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia [PDF]
BMC Public HealthIntroduction Dengue is a mosquito-borne disease caused by the dengue virus, primarily transmitted by Aedes aegypti and Aedes albopictus. Its incidence fluctuates due to spatial and temporal factors, necessitating robust modeling approaches for prediction
Marko Ferdian Salim +2 more
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ISPRS International Journal of Geo-Information, 2016 This research investigates spatio-temporal patterns of police calls-for-service in the Region of Waterloo, Canada, at a fine spatial and temporal resolution. Modeling was implemented via Bayesian Integrated Nested Laplace Approximation (INLA).
Hui Luan, Matthew Quick, Jane Law
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Bayesian Model Averaging with the Integrated Nested Laplace Approximation
Econometrics, 2020 The integrated nested Laplace approximation (INLA) for Bayesian inference is an efficient approach to estimate the posterior marginal distributions of the parameters and latent effects of Bayesian hierarchical models that can be expressed as latent ...
Virgilio Gómez-Rubio +2 more
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Application of integrated nested Laplace approximation to identify hot spots of methylation heterogeneity in healthy individuals from the MAMELI cohort [PDF]
Frontiers in GeneticsDNA methylation is an epigenetic regulator of gene expression and cell identity, which can be shaped by both physiological and pathological factors, including environmental exposure.
Tiago Nardi +7 more
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An Approximate Bayesian Inference for Beta Regression Models [PDF]
Journal of Sciences, Islamic Republic of Iran, 2022 In modeling the variables related to each other, regression models are usually used assuming that the response variable is Normal. But in problems dealing with data such as the rate or ratio of an event distributed in the (0,1) interval, these models may
kobra Gholizadeh Gazvar +1 more
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Bayesian spatio-temporal modeling for policy evaluation: Sensitivity of policy effect estimates in the context of COVID-19 stay-at-home orders. [PDF]
PLoS ONEThis study applies a Bayesian spatio-temporal model to demonstrate the sensitivity of policy effect estimates to spatial and temporal structure, using COVID-19 stay-at-home orders as a case study.
Pyung Kim +3 more
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Estimating Spatial Econometrics Models with Integrated Nested Laplace Approximation
Mathematics, 2021 The integrated nested Laplace approximation (INLA) provides a fast and effective method for marginal inference in Bayesian hierarchical models. This methodology has been implemented in the R-INLA package which permits INLA to be used from within R ...
Virgilio Gómez-Rubio +2 more
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Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling
BMC Public Health, 2022 Background Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. It is caused by the ingestion of food or water and infected all age groups.
Tsigereda Tilahun Letta +2 more
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Laplace approximation for conditional autoregressive models for spatial data of diseases
MethodsX, 2022 Conditional autoregressive (CAR) distributions are used to account for spatial autocorrelation in small areal or lattice data to assess the spatial risks of diseases.
Guiming Wang
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