Sentence examples for maximum entropy test from inspiring English sources

The objective of this study is to develop a robust maximum entropy test for the normality of GARCH models.

In this paper, we apply the maximum entropy test designed for a goodness of fit in iid samples (cf. Lee et al. (2011)) to GARCH 1,1) models.

The maximum entropy test, as designed for examining goodness-of-fit with a non-robust estimator such as the maximum likelihood estimator, can suffer from severe size distortions when the data are contaminated by outliers.

The two- and higher-dimensional maximum entropy test problems in the current work are based upon long-term statistics of numerical simulation of the real-world geophysical model for wind stress driven oceanic currents such as the Gulf Stream and the Kuroshio.

As a gof test based on this result, the maximum entropy type test designed by Lee et al.

One could define a null model using the Maximum Entropy Principle [33] and test whether the results shown in the paper still hold.

Statistical classification techniques used for recognition include those based on the minimum distance [22], similarity score [33], Kullback Leibler distance [34], maximum a posteriori (MAP) model [15, 32], maximum entropy [30], likelihood dependency test [21], support vector machine [17], and nearest neighbor classifier [10, 35].

Based on presence-only data, two inductive predictive modelling approaches, i.e., a geographical information system (GIS -based multiparametric spatial analysis (MPSA) and maximum entropy model (MaxEnt), were tested, inteGIS -based evaluated for archaeological applications at different scales over the case study area of the Tavoliere Plain (Southern Italy).

For this reason, we tested the maximum entropy algorithm, Maxent, which is one of the leading algorithms for species habitat modeling [12],[30]-[32], to map deforestation likelihood.

For this reason, we tested the maximum entropy algorithm, Maxent, which is one of the leading algorithms for species habitat modeling [ 12],[ 30]-[ 32], to map deforestation likelihood.

The various degree distributions considered here are tested against a maximum entropy (MaxEnt) distribution [29].