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Showing 1 to 20 of 23 for “"Bayesian Information Criterion: BIC)"”.
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Clustering Analysis of Zernike Coefficients From High Order Aberration Patients
… estimate of parameters for each cluster. Bayesian information criterion (BIC) combined with Bootstrapped maximum volume (BMV) criterion are used to determine the number of clusters. The Bootstrap method is used to estimate the uncertainty on the number of clusters. These fifteen Zernike …
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Clustering Analysis of Zernike Coefficients Through Quantile Regression
… to infer the parameters for each cluster. Bayesian information criterion (BIC) combined with a measure of uncertainty are used to determine the number of clusters. A comparison of likelihoods between the unclustered and the clustered Zernike coefficients is implemented to determine the …
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Bayesian model determination for categorical data survey
… this thesis is to present an investigation of a Bayesian approach to the analysis of categorical survey data, arising from designs including simple random sampling, finite population sampling, stratification, and cluster sampling. We focus on Bayesian methods for model selection and model …
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Bayesian Methodology for Missing Data, Model Selection and Hierarchical Spatial Models with Application to Ecological Data
… are assumed normally distributed we use the Bayesian Model Averaging method to average the models, select the highest probability model and do variable assessment. Accuracy in calculating the posterior model probabilities using the Laplace approximation and an approximation based on the …
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Parametric survival models with interval censored data in determining prognostic factors of patients of lung cancer
… and number of sample sizes. Besides, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Corrected Akaike Information Criterion (AICC) been evaluated in finding the best fit model towards the survival time of lung cancer. Thus, the exponential model was found to be the …
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Model selection in rheology: Providing a practical framework, surveying the field, and assessing the uses and limitations of BIC
… the application of simple criteria such as the Bayesian Information Criterion (BIC) may add significant value and validity to these analyses. There remains even greater opportunity in the application of more sophisticated methods such as the calculation of Bayes Factors and the formulation of …
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Assessing the Effect of “Time of Birth” on Nasopharyngeal Microbial Load in Infants
… repeated measures. Model selection was based on Bayesian Information Criterion (BIC). MOB showed a statistically significant non-linear relationship with Moraxella microbial abundance (p < 0.001). Increasing age and birth order were positively associated with the outcome (p < 0.001 and p = 0.03 …
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Zircon crystallization patterns from U-Th dates inform U-Pb estimates of volcanic eruption ages
… sample and evaluates the fit of each model using Bayesian Information Criterion (BIC). Our results show that, while the crystallization history of 56 of 137 zircon data populations remains unresolved even with sub-10 ka absolute date uncertainties, most resolvable models’ crystallization histories …
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Topics In Time Series Analysis And Forecasting
… of the commonly used selection criteria, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), are discussed. In the finite case, the study is limited to the two sample problem. The exact probability of selection is obtained for finite samples. The risk of each criterion is …
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Complexity analysis of lumped parameter models : development of complexity reduction algorithm
… complexity and the results by using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) as an indicator for model selection have been shown.
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Variants of compound models and their application to citation analysis
… based on log-likelihood methods, Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The suitability of the models is also assessed using two diagrammatic methods, randomised quantile residual plots and Christmas tree plots. The Christmas tree plots clearly …
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Comparison of parametric models using right censored data for breast cancer patients
… on the value obtained from corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and mean square error (MSE). Based on the model selections, the log-logistic model found to be the best model with smallest value in AICc, BIC, and MSE. Besides that, a simulation …
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Bayesian model averaging on hydraulic conductivity estimation and groundwater head prediction
… of model parameters. This study introduces a Bayesian model averaging (BMA) method along with multiple generalized parameterization (GP) methods to identify hydraulic conductivity and along with multiple simulation models to predict groundwater head and quantify the prediction uncertainty. Two …
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Cognitive Diagnostic Model, a Simulated-Based Study: Understanding Compensatory Reparameterized Unified Model (CRUM)
… (CDM) has the potential to provide valuable information for stakeholders to assist students identify their skill deficiency in specific academic subjects. Cognitive diagnosis models are mainly viewed as a family of latent class confirmatory probabilistic models. These models allow the mapping …
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Mixed Mode Latent Class Clustering: An Examination of Fit Index Performance for Identifying Latent Classes
… The fit indices examined were Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), sample size-adjusted Bayesian Information Criterion (SSBIC), Entropy, Integrated Classification Likelihood Criterion with Bayesian-type Approximation, Lo-Mendell-Rubin likelihood …
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Modeling and Forecasting Ghana's Inflation Rate Under Threshold Models
… were employed and fitted to the data. The Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) were used to assess each of the fitted models such that the model with the minimum value of AIC and BIC, was judged the best model. Additionally, the fitted models were …
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Rheological inferences with uncertainty quantification
… is a valuable tool for inferring microstructural information from rheology. In this work, we focus on the asymptotically-nonlinear medium-amplitude oscillatory shear (MAOS) data, the next systematic step after small-amplitude oscillatory shear (SAOS). The first part of this research is composed of …
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Associated factor of mortality rate amongst patients with AIDS and HIV-TB co-infections using zero inflated negative binomial method
… of model superiority. In addition, the Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC) values were used to compare the fit between models. The results suggested that the literature are not entirely anomalous. However, the accuracy of the findings depended on the …
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ESTIMATING UNKNOWN KNOTS IN PIECEWISE LINEAR-LINEAR LATENT GROWTH MIXTURE MODELS
… 3-class piecewise linear-linear LGMMs) using the Bayesian Information Criterion (BIC) was examined. Results suggested that the recovery of model parameters, specifically, the variances of growth factors were generally poor. In addition, none of the manipulated conditions were systematically …
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An Evaluation of the Physical Demands of American Football Training in the NFL
… logistic regression models were compared using Bayesian Information Criterion (BIC). The best model suggested that sessions with greater volume (PLTotal) and intensity (ImpactsHigh) were associated with non-contact soft tissue injury in American football players and may have implications for …
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