Results 91 to 100 of about 137,667 (314)

Approximating the Likelihood in Approximate Bayesian Computation

, 2018
This chapter will appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). The conceptual and methodological framework that underpins approximate Bayesian computation (ABC) is targetted primarily towards problems in which the likelihood is either challenging or missing.
Drovandi, Christopher C, Grazian, Clara, Mengersen, Kerrie, Robert, Christian   +3 more
openaire   +2 more sources

Approximate Bayesian Computation for infectious disease modelling [PDF]

Epidemics, 2019
Approximate Bayesian Computation (ABC) techniques are a suite of model fitting methods which can be implemented without a using likelihood function. In order to use ABC in a time-efficient manner users must make several design decisions including how to code the ABC algorithm and the type of ABC algorithm to use.
Minter, Amanda, Retkute, Renata
openaire   +3 more sources

Biopsychosocial Determinants of Hand Function and Its Trajectories Over Five Years in Patients With Hand Osteoarthritis

Arthritis Care &Research, EarlyView.
Objective This study aimed to investigate hand function trajectories over five years in primary hand osteoarthritis (OA). Additionally, determinants of baseline and longitudinal hand function were assessed. Methods A total of 538 patients with both baseline and five‐year study visits were analyzed.
Annemiek V. E. M. Olde Meule, Coen van der Meulen, Jos Runhaar, Frits R. Rosendaal, Margreet Kloppenburg   +4 more
wiley   +1 more source

Obesity Subtypes and Longitudinal Trajectories of Function Over Seven Years of Follow‐Up: Data From the Multicenter Osteoarthritis Study

Arthritis Care &Research, EarlyView.
Objective Obesity, defined by body mass index (BMI) ≥30 kg/m2, is a risk factor for functional limitations in people with knee osteoarthritis (OA). However, function varies among such individuals. Our objective was to evaluate the implications of obesity subtypes on longitudinal patterns of physical functioning in people with or at risk for knee OA ...
Kristine Godziuk, Sarah Tilley, Michael LaValley, Michael C. Nevitt, Cora E. Lewis, James C. Torner, Tuhina Neogi, for the Multicenter Osteoarthritis Study Group   +7 more
wiley   +1 more source

Inferring state‐dependent diversification rates using approximate Bayesian computation

Methods in Ecology and Evolution
State‐dependent speciation and extinction (SSE) models are a popular framework for quantifying whether species traits have an impact on evolutionary rates and how this shapes the variation in species richness among clades in a phylogeny.
Shu Xie, Luis Valente, Rampal S. Etienne
doaj   +1 more source

Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate Bayesian computation and steady-state signalling simulations

BMC Bioinformatics, 2020
Background Network inference is an important aim of systems biology. It enables the transformation of OMICs datasets into biological knowledge.
Antoine Buetti-Dinh, Malte Herold, Stephan Christel, Mohamed El Hajjami, Francesco Delogu, Olga Ilie, Sören Bellenberg, Paul Wilmes, Ansgar Poetsch, Wolfgang Sand, Mario Vera, Igor V. Pivkin, Ran Friedman, Mark Dopson   +13 more
doaj   +1 more source

Clinical, histological, and serological predictors of renal function loss in lupus nephritis.

Arthritis Care &Research, Accepted Article.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang, Laurence Magder, Daniel Goldman, Judith A. James, Joel M Guthridge, Carla Guthridge, Peter Izmirly, Jill P Buyon, H.Michael Belmont, Richard A. Furie, Noa Schwartz, Chaim Putterman, Jennifer L. Barnas, Jennifer H. Anolik, Sarah French, Maria Dall'era, Avi Z. Rosenberg, Jeffrey Hodgin, Dawit S. Demeke, the Accelerating Medicines Partnership RA/SLE Network, Michelle Petri, Andrea Fava   +21 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Approximate Bayesian Computation for Estimating Parameters of Data-Consistent Forbush Decrease Model

Entropy, 2018
Realistic modeling of complex physical phenomena is always quite a challenging task. The main problem usually concerns the uncertainties surrounding model input parameters, especially when not all information about a modeled phenomenon is known.
Anna Wawrzynczak, Piotr Kopka
doaj   +1 more source

Probabilistic Updating of Structural Models for Damage Assessment Using Approximate Bayesian Computation

Sensors, 2020
A novel probabilistic approach for model updating based on approximate Bayesian computation with subset simulation (ABC-SubSim) is proposed for damage assessment of structures using modal data.
Zhouquan Feng, Yang Lin, Wenzan Wang, Xugang Hua, Zhengqing Chen   +4 more
doaj   +1 more source