Sentence examples for faithful distribution from inspiring English sources

Assuming a faithful distribution to G and perfect CI tests, PC correctly infers the skeleton of G [ 14], regardless of order(V).

If the graph is faithful to the distribution, then X and Y will be probabilistically dependent conditional upon any set containing Z.

Overall, the results indicate that the orbital trap measured m/ z distributions were faithful, unbiased representations of the true peptide mass distributions.

Yielding satisfactory results with sufficiently concentrated posterior distributions, such methods fall short of providing a faithful summary of posterior distributions if the data do not offer compelling evidence for a single topology.

The peat landforms visible on aerial photographs and satellite imagery provide a faithful indicator for the distribution of different groundwater flow systems over the landscape since raised bog landforms are consistently associated with groundwater mounds and recharge systems, whereas fen landforms are found in zones of discharge or lateral flow.

And in this case, the average is a faithful representation of the distribution, with only one Democrat in the minus column and only one Republican in the plus.

IDA and all its extensions require among other assumptions that the multivariate Gaussian distribution is faithful to the DAG (Kalisch and Bühlmann, 2007), i.e. statistical conditional independencies can be inferred from the underlying DAG.

Additionally, Tsamardinos and Aliferis [ 46] considered the connection between KJ-relevance and the Markov blanket of a target variable in a Bayesian Network faithful to some data distribution, which aims at building the minimal subset of features according to the following definition: Markov Blanket.

With regards to the first assumption (relaxed faithfulness), prior research has established that non-faithful discrete probability distributions are extremely rare, and therefore it is reasonable to make this assumption here [ 46].

The SOM learning also provides a faithful representation of the data distribution on the prototype level, which can be controlled by a magnification parameter with slight changes in the learning algorithm [31].

In this work, a new method of particle remapping is presented which strictly conserves mass, momentum, and energy while simultaneously remaining faithful to the original velocity distribution function through the use of octree binning in velocity space.