Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach

Oakley, Jeremy E.; O'Hagan, Anthony

doi:10.1111/j.1467-9868.2004.05304.x

Cited by 947 publications

(781 citation statements)

References 27 publications

Supporting

Mentioning

772

Contrasting

Unclassified

Order By: Relevance

“…We calculated sensitivity indices (main effect of each input on the response) for each variable to assess their relative influence using GPM/SA (Los Alamos National Laboratory, Los Alamos, NM). 25 Additionally, main effect plots (trend of the response over the range of each input) were created for variables with large sensitivity indices.…”

Section: Discussionmentioning

confidence: 99%

Hip resurfacing increases bone strains associated with short‐term femoral neck fracture

Long

Santner

Bartel

2009

Journal Orthopaedic Research

View full text Add to dashboard Cite

Short-term femoral neck fracture is a primary complication associated with contemporary hip resurfacing. Some fractures are associated with neck notching, while others occur in the absence of notching. These unexplained fractures may be due to large magnitude strains near the implant rim, which could cause bone damage accumulation and eventual neck fracture. We used statistically augmented finite element analysis to identify design and environmental variables that increase bone strains near the implant rim after resurfacing, and lead to strain magnitudes sufficient for rapid damage accumulation. After resurfacing, the compressive strains in the inferior, peripheral neck increased by approximately 25%, particularly when the implant shell was bonded. While the tensile strains in the peripheral neck were low in magnitude in the immediate postoperative models, they increased substantially following compressive damage accumulation. Low bone modulus, within the range of normal bone, and high head load contributed the most to large magnitude strains. Therefore, in some cases, hip resurfacing may cause a region of compressive bone damage to develop rapidly, which in turn leads to large tensile strains and potential neck fracture. Our study suggests that indications for surgery should account for bone material quality, and that rehabilitation protocols should avoid high-load activities. ß

show abstract

Section: Discussionmentioning

confidence: 99%

Hip resurfacing increases bone strains associated with short‐term femoral neck fracture

Long

Santner

Bartel

2009

Journal Orthopaedic Research

View full text Add to dashboard Cite

show abstract

“…Many opportunities appear here to improve the performance of emulators: one could think of including multiple pieces of information in the regression algorithm with multimodal/multiresolution regression, e.g., by combining RTMs for the same problem, to accommodate spatial or temporal relations in the emulation [44,94], and to implement better dimensionality reduction techniques beyond linear PCA to deal with the multi-output problem [95]. Apart from these improvements in the regression algorithm, we raise here the important issue of assessment of the emulator function, e.g., by looking at the Jacobian and Hessian of the transformation [38,96], Bayesian sensitivity analysis [34,97], as well as developing emulators that may deal with coupled RTMs and transformations of coefficients [50].…”

Section: New Processing Opportunities With Emulatorsmentioning

confidence: 99%

Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

et al. 2016

View full text Add to dashboard Cite

Abstract:Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome, which makes them impractical in many real applications, especially when many state conditions and model couplings need to be studied. To overcome this problem, it is proposed to substitute RTMs through surrogate meta-models also named emulators. Emulators approximate the functioning of RTMs through statistical learning regression methods, and can open many new applications because of their computational efficiency and outstanding accuracy. Emulators allow fast global sensitivity analysis (GSA) studies on advanced, computationally expensive RTMs. As a proof-of-concept, three machine learning regression algorithms (MLRAs) were tested to function as emulators for the leaf RTM PROSPECT-4, the canopy RTM PROSAIL, and the computationally expensive atmospheric RTM MODTRAN5. Selected MLRAs were: kernel ridge regression (KRR), neural networks (NN) and Gaussian processes regression (GPR). For each RTM, 500 simulations were generated for training and validation. The majority of MLRAs were excellently validated to function as emulators with relative errors well below 0.2%. The emulators were then put into a GSA scheme and compared against GSA results as generated by original PROSPECT-4 and PROSAIL runs. NN and GPR emulators delivered identical GSA results, while processing speed compared to the original RTMs doubled for PROSPECT-4 and tripled for PROSAIL. Having the emulator-GSA concept successfully tested, for six MODTRAN5 atmospheric transfer functions (outputs), i.e., direct and diffuse at-surface solar irradiance (E di f , E dir ), direct and diffuse upward transmittance (T dir , T di f ), spherical albedo (S) and path radiance (L 0 ), the most accurate MLRA's were subsequently applied as emulator into the GSA scheme. The sensitivity analysis along the 400-2500 nm spectral range took no more than a few minutes on a contemporary computer-in comparison, the same analysis in the original MODTRAN5 would have taken over a month. Key atmospheric drivers were identified, which are on the one hand aerosol optical properties, i.e., aerosol optical thickness (AOT), Angstrom coefficient (AMS) and scattering asymmetry variable (G), mostly driving diffuse atmospheric components, E di f and T di f ; and those affected by atmospheric scattering, L 0 and S. On the other hand, as expected, AOT, AMS and columnar water vapor (CWV) in the absorption regions mostly drive E dir and T dir atmospheric functions. The presented emulation schemes showed very promising results in replacing costly RTMs, and we think they can contribute to the adoption of machine learning techniques in remote sensing and environmental applications.

show abstract

“…The Bayesian approach has been progressively included in the formal assessment of uncertainty [12][13][14][15] and applied in the value-of-information framework [16]. It nevertheless remains that its handling by HTA guidelines remains tricky and challenging.…”

Section: From the Knightian To The Bayesian Uncertaintymentioning

confidence: 99%

Towards a New Framework for Addressing Structural Uncertainty in Health Technology Assessment Guidelines

Ghabri¹,

Cleemput

Josselin

2017

PharmacoEconomics

View full text Add to dashboard Cite

International audienceProviding scientific advice and recommendations for public decision making entails identifying, selecting and weighing evidence derived from multiple sources of information through a systematic approach, while taking into account ethical, cultural and societal factors. Integrated in the evaluation process are exchanges between regulatory agencies, private firms, scientific experts and government representatives. In the case of drugs and medical devices, health technology assessment (HTA) agencies are increasingly commissioned to evaluate innovations in order to provide government with recommendations and advice on reimbursement and/or pricing. To undertake this task, HTA agencies [1–6] in Europe and elsewhere have developed methodological guidelines on the economic evaluation of health technologies [7]. One component of these guidelines deals with ways for both manufacturers (pharmaceutical and medical device firms) and HTA agencies evaluators (modelers, economists and public health experts) to address uncertainty. Several types of uncertainty have indeed been identified in HTA: methodological, parameter and structural uncertainty. Most guidelines describe quite well how to deal with the first two categories, although there is still room for improvement. However, recommendations about how to tackle structural uncertainty remain largely elusive. HTA agencies and decision makers may thus be exposed to oversimplifying assessments and recommendations by putting aside complex forms of uncertainty such as struc-tural ‘deep’ uncertainty [8]. The editorial is not intended to promote new approaches to exploring structural uncertainty, rather to emphasizeconcerns related to the topic, such as definition and analysis. Our aim is therefore to highlight the need to renew the analytical framework guidance for HTA

show abstract

Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach

Cited by 947 publications

References 27 publications

Hip resurfacing increases bone strains associated with short‐term femoral neck fracture

Hip resurfacing increases bone strains associated with short‐term femoral neck fracture

Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis

Towards a New Framework for Addressing Structural Uncertainty in Health Technology Assessment Guidelines

Contact Info

Product

Resources

About