A Bayesian approach with generalized ridge estimation for high-dimensional regression and testing.
Szu-Peng YangTakeshi EmuraPublished in: Commun. Stat. Simul. Comput. (2017)
Keyphrases
- high dimensional
- estimation problems
- regression model
- generalized linear models
- ordinary least squares
- semi parametric
- nearest neighbor
- multi variate
- nonparametric regression
- robust regression
- high dimensional data
- support vector regression
- singular points
- accurate estimation
- gaussian processes
- estimation algorithm
- parameter estimation
- support vector
- data points
- dimensionality reduction
- density estimation
- high dimensionality
- linear regression
- regression analysis
- software testing
- logistic regression
- estimation accuracy
- simple linear
- genetic programming
- discrete data
- intrinsic dimensionality
- low dimensional
- ridge regression
- least squares
- neural network
- feature space
- statistical tests