Sentence examples for information criterion for from inspiring English sources

The Deviance Information Criterion (DIC) is perhaps the most general of such methods, being a generalisation of the Akaike information criterion for Bayesian hierarchical models [20].

A new Bayesian approach is proposed to perform this task, based on the Kashyap information criterion for model selection.

Multivariate regressions demonstrated larger hazard ratios (HRs) and a lower Akaike information criterion for the pN model versus the AJCC stage and LNR models.

Specifically, we found the lowest Akaike's Information Criterion for K+, pH, total P, and nitrate at scales of 5, 20, 30, and 40 m, respectively.

For Poisson data and log-linear regression, similar assessments are made using maximum likelihood and the Akaike information criterion for minimally-supported designs that are constructed analytically.

These considerations permit to formulate the quantum information criterion for the new predicting system (NS) and the subsystems (functioning sewage treatment system, OS) and (additional system, AS).

†for the existing time-dependent model with no trend indicators * p-value from the likelihood ratio test comparing the existing time-dependent model with and without the trend indicator **Akaike's Information Criterion ‡For all trend indicators, the value was expressed as a positive or negative number for an increase or decrease in the risk score, respectively.

As discussed below, the use of the Bayesian Information criterion (BIC) or the Akaike Information criterion for estimating clusters is problematic.

Section 6 discusses the implications of a Fisher Information criterion for Likert scale interpretation, and draws conclusions germane to future survey design.

In addition, they both generate mutually exclusive and exhaustive classes, use an objective technique to determine the number of classes (Bayesian Information Criterion for LCA or Schwartz Bayesian criteria for TwoStep Clustering), and work with categorical and continuous variables.

For both mechanistic model types (precipitation and age of bedrock), we evaluated the strength of mixed-effects versus fixed-effects models using Akaike's Information Criterion for small sample sizes (AICc) and evidence ratios (ER = e0.5*ΔAICc; [44].