Bayesian variable selection in generalized linear models using a combination of stochastic optimization methods
Abstract
Abstract is not available.- Bayesian variable selection
- Genetic algorithm
- Laplace approximation
- Simulated annealing
- Stochastic optimization
- Tabu search
- Computational costs
- Criterion functions
- Generalized linear model
- Logistic regression models
- Model composition
- Model probabilities
- Model search
- Stochastic optimization algorithm
- Stochastic optimization methods
- Stochastic optimizations
- Approximation algorithms
- Computer simulation
- Laplace transforms
- Logistics
- Regression analysis
- Stochastic models
- Stochastic systems
- Genetic algorithms
- Bayesian variable selection
- Genetic algorithm
- Laplace approximation
- Simulated annealing
- Stochastic optimization
- Tabu search
- Bayesian variable selection
- Computational costs
- Criterion functions
- Generalized linear model
- Laplace approximation
- Logistic regression models
- Model composition
- Model probabilities
- Model search
- Stochastic optimization algorithm
- Stochastic optimization methods
- Stochastic optimizations
- Approximation algorithms
- Computer simulation
- Laplace transforms
- Logistics
- Regression analysis
- Simulated annealing
- Stochastic models
- Stochastic systems
- Tabu search
- Genetic algorithms
Similar works
Full text
Last time updated on 03/06/2016
This paper was published in DSpace@NTUA (National Technical Univ. of Athens).
Having an issue?
Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.