Bayesian prediction
Gibbs Sampling for Bayesian Prediction of SARMA Processes
... a Bayesian prediction of multiplicative seasonal autoregressive moving average (SARMA) processes using the Gibbs sampling ...proposed Bayesian method using simulation study and real-world time series ...
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Bayesian Prediction under a Finite Mixture of Generalized Exponential Lifetime Model
... studied Bayesian prediction under a finite mixture of two component Gompertz lifetime model, based on type-I censored ...discussed Bayesian prediction under generalized exponential ...
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Parameter Estimation of Smart Grid using PMU with Kalman Filter and Bayesian Prediction
... Soumitra Kumar Sarker is a student of Alakh Prakash Goyal Shimla University, Himachal Pradesh, India. At present the author is pursuing Master of technology in Electrical Engineering (Power System). Currently he is ...
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Non-linear Bayesian prediction of generalized order statistics for liftime models
... obtain Bayesian prediction intervals as well as the Bayes predictive estimators for GOS when the distribution of the underlying population belongs to a family which includes several important distributions ...
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Asymptotic multivariate kriging using estimated parameters with bayesian prediction methods for non-linear predictands
... The prediction intervals for a single observation are easily ...a prediction interval is calculated for a normally distributed variable and then the transformation is ...a prediction that depends on ...
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Bayesian Inference and Prediction for Normal Distribution Based on Records
... and prediction for normal dis- tribution based on record data in the Bayesian set ...well. Bayesian prediction of future records based on the first few upper records is also ...
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O pt i ma l i t yo f Uni v e r s a l Ba y e s i a n Se q ue nce P r e di ct i o n f o r Ge ne r a l L o s sa nd Al pha be t
... Many prediction schemes explicitly learn and exploit a model of the ...universal Bayesian pre- ...for Bayesian prediction, so maybe the proof technique presented here could be used vice versa ...
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Prediction Based on Generalized Order Statistics from a Mixture of Rayleigh Distributions Using MCMC Algorithm
... [24] K. E. Ahmad, Z. F. Jaheen and Heba S. Mohammed, “Bayesian Prediction Based on Type-I Censored Data from a Mixture of Burr Type XII Distribution and Its Re- ciprocal,” Statistics, Vol. 1, No. 1, 2011, ...
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A review on football match outcome prediction using Bayesian networks
... Other Bayesian network model for forecasting match was is presented in [12]. The data used for training were the English Premier League season 1993/1994 to 2009/2010. The two types of features used the objective ...
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Heart Disease Prediction using Machine Learning
... In the proposed study, we developed a machine-learning-based diagnosis system for heart disease prediction by using heart disease dataset. we present a brief overview of ML methodologies that are used for the ...
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Bayesian latent variable models for collaborative item rating prediction
... As noted in section 2, the most successful models compet- ing in the Netflix prize also estimate a bias for each user and a bias for each item as well as the bias due to the user and the item together. This is a sensible ...
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Bayesian applications in econometrics
... Although only a few such problems are dealt with in the thesis, the results obtained demonstrate some of the features of Bayesian inference as they relate to estimation, prediction, prio[r] ...
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A nonparametric Bayesian approach for counterfactual prediction with an application to the Japanese private nursing home market
... nonparametric Bayesian statistics, applied econometrics for the industrial organization field, and empirical studies of elder ...intensive Bayesian methodologies such as the Markov chain Monte Carlo(MCMC), ...
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Predictive Analysis of Microarray Data
... Data from a typical microarray experiment consist of positive numbers representing the expression levels of the genes associated with the microarray probes for a group of individuals. Because the convoluted nature of the ...
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Improving Type II Diabetes Prediction Using Bayesian Optimization
... the Bayesian Neural Network architecture is used for predictive analysis of type II ...performed. Bayesian Regularization showed the best results against the other algorithms, in terms of accuracy and error ...
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A two step Bayesian approach for genomic prediction of breeding values
... Methods: The simulated data from the 15 th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers ...
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Bayesian posterior prediction and meta analysis: an application to the value of travel time savings
... Bayesian posterior prediction and meta-analysis: an application to the value of travel time savings.[r] ...
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Credit Card Fraud Detection using Hybrid Models
... The main part of the proposed system is the master data manger module or the admin module. The administrator controls the whole part of the system. It manages various credit card types, Credit Card Company, Vendor ...
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Bayesian accrual prediction for interim review of clinical studies: open source R package and smartphone application
... on a weekly or monthly basis. The accrual software can be used for prediction at any time during the trial. The re- sults will help investigators, sponsors, and oversight com- mittees objectively evaluate the ...
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Prediction distribution for linear regression model with multivariate Student-t errors under the Bayesian approach
... obtain prediction distributions for different ...the prediction distribution(s) for multiple linear regression model using the Bayesian method when the error components of both the performed and ...
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