[PDF] Top 20 A hierarchical Bayesian approach for parameter estimation in HIV models
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A hierarchical Bayesian approach for parameter estimation in HIV models
... and the references therein), use of such models in HIV pathogenesis studies is more recent [14, 15, 16, 24, 29, 30]. Early uses [14, 15, 30] involved simplification of the models to obtain closed ... See full document
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Hierarchical Bayesian Estimation of System Parameters from Dynamic Responses
... A hierarchical Bayesian approach is proposed for estimating system parameters by directly taking dynamic responses as the fixed ...of hierarchical Bayesian model are first introduced, ... See full document
6
Bayesian estimation of agent based models
... on estimation of AB ...the estimation of the model described in Brock and Hommes ...SMD approach leads to alternative estimators with respect to those commonly employed in the literature, such as MSM ... See full document
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A Comparison of Hierarchical Bayesian Models for Small Area Estimation of Counts
... simplest approach is to consider direct estimators, that is estimating the variable of interest using the domain-specific sample ...area models that “borrow strength" from related areas across space ... See full document
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Bayesian model selection and parameter estimation for fatigue damage progression models in composites
... mechanics models can be found in the litera- ture [23]. These models, that are grounded on first principles of admissible ply stress fields in presence of damage, can be roughly classified into 1) ... See full document
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Bayesian Approach in Estimation of Shape and Scale Parameter of Log-Weibull model
... Model selection encompasses many aspects. There are a number of distributions useful for modeling reliability data. For example, for analyzing failure times, most applications choose from the exponential, Weibull, or ... See full document
12
Coupled hydrogeophysical parameter estimation using a sequential Bayesian approach
... Two versions of the filter were run with different obser- vation models. In the first version, the observation model simply compared modelled and measured soil water con- tent derived from spatial TDR. The second ... See full document
12
Bayesian Skew Normal Seemingly Unrelated Regression Modelling of Gross Regional Domestic Product
... using Bayesian approach applied to East Java GRDP ...of models, namely models with Normal distributed errors and models with Skew Normal distributed ...of parameter ... See full document
11
Bayesian methods for hierarchical distance sampling models
... two-stage approach – the likelihoods for both components of our model were combined for the integrated likelihood and influence each ...simultaneous estimation of all parameters in one stage represents a ... See full document
32
Improved Simultaneous Estimation of Location and System Reliability via Shrinkage Ideas
... (LT) models are a broad class of regression models which take the PH, PO, and PB models as special ...LT models presume that an unknown non-decreasing transformation function of failure time ... See full document
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Bayesian Approach in Estimation of Scale Parameter of Nakagami Distribution
... parametric models are used in the analysis of lifetime data and in problems related to the modeling of failure ...univariate models, a few particular distributions occupy a central role because of their ... See full document
12
Bayesian Hierarchical Spatial-Temporal Models for Wind Prediction
... geostatistics approach is based on spatial processes which are sta- tionary , but it is widely recognized that real environmental processes are rarely ...nonparametric estimation procedure for nonstationary ... See full document
108
Risk parameter estimation in volatility models
... GARCH-type models dealt exclusively with the estimation of volatility ...QML estimation for volatility parameters has been exten- sively studied, in particular for the GARCH(1,1) by Lee and Hansen ... See full document
43
Using Bayesian methods for the parameter estimation of deformation monitoring networks
... two estimation procedures “Bayes-Updating” and “Gibbs-Sampling” based on Bayes theory for deformation monitoring networks which allows accounting for prior information about the coordinate param- ...of ... See full document
13
Parameter estimation via conditional expectation: a Bayesian inversion
... general approach for state and parameter estimation has been presented in a Bayesian ...The Bayesian approach is based here on the conditional expectation (CE) operator, and ... See full document
21
Sparse Bayesian blind image deconvolution with parameter estimation
... variational Bayesian based maximization (see [25] for an example derivation) for the special case when all the posterior distributions are assumed to be ... See full document
15
Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy
... a hierarchical Bayesian framework. Bayesian hierarchical models with a heterogeneity and a clustering term allowed for unmeas- ured or unknown risk ... See full document
16
EM based parameter iterative approach for sparse Bayesian channel estimation of massive MIMO system
... channel estimation scheme is proposed to further reduce the pilot overhead and improve the estimation ...sparse Bayesian learn- ing [8] has been developed to estimate the sparse channel ... See full document
7
Parameter calibration in global soil carbon models using surrogate-based optimization
... new parameter point generation. Most strategies con- vert the parameter point generation to optimization problems using an evaluation criterion ...new parameter point to evaluate the real simulation ... See full document
18
Hierarchical Bayesian application to instantaneous rates tag-return models
... (28). Bayesian methods allow one examine the impacts of a variety of priors on the inference of a ...improve estimation for very small datasets. The improvement in estimation for small datasets may ... See full document
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