Sentence examples for regression and inference from inspiring English sources

Herein, we discuss two unified regression and inference approaches, model II regression and regression calibration, for use in massively univariate inference with imaging data.

Massively univariate regression and inference in the form of statistical parametric mapping have transformed the way in which multi-dimensional imaging data are studied.

Usual cointegrating regression theory and inference continues to hold in spite of the degeneracy in the limit theory and is therefore robust to initial conditions that extend to the infinite past.

The research investigates a statistical procedure to inversely estimate building parameters using regression and Bayesian inference model based on the Markov Chain Monte Carlo (MCMC) sampling techniques.

The energy performance of buildings was estimated using various data mining techniques, including support vector regression (SVR), artificial neural network (ANN), classification and regression tree, chi-squared automatic interaction detector, general linear regression, and ensemble inference model.

Logistic regression and multimodel inference using Akaike's information criteria were used to identify potentially important predictor variables influencing the distribution of the northern long-eared bat at the fragment and landscape level and quantified their effects.

Sparsity (presence of a many zero entries in a vector or matrix) has been exploited in a wide range of applications including sparse regression and statistical inference, e.g., see [21, 22].

In this paper we investigate the performance of traditional (stepwise regression using AIC, BIC, and the Likelihood Ratio Test) and some of the alternative (BMA, lasso, adaptive lasso, and adaptive elastic net) methods of subset selection in linear regression and making inferences about regression coefficients.

Whilst the appropriate variance function may be identified from the modified Park test, one obtains different regression coefficients and inferences on incremental/marginal effects as the link function selected varies.

Soc500 covers probability, regression and basic causal inference.

This article proposes a new framework for Bayesian isotonic regression and order restricted inference.