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The goal here is to characterize the importance of each predictor for a given random forest.

where x ˜ u, 0 is a given random variable with E ( | x ˜ u, 0 | 2 ) < ∞ for each u ∈ [ 0, 1 ].

After statistical analysis of maximum axial forces from all experiments, the average maximum axial-force interval that the remaining bolts can withstand under a given random condition is estimated with a 95% confidence level.

Here, x 0 is a given random variable taking values in R, which is independent of F ∞ B with E ( | x 0 | 2 ) < ∞. α and β are unknown drift parameters, while σ is an unknown diffusion coefficient.

Mathematical expectation is denoted by E; Pr stands for probability; f W and F W represent the probability density function (PDF) and cumulative distribution function (CDF) of a given random variable (RV) W, respectively.

Autoregressive (AR) models have been the workhorse for parametric spectral estimation since they form a dense set in the class of continuous spectra and, in many cases, they approximate parsimoniously the spectrum of a given random process [1], Chap.

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EM quickly converged to an activated level when trained with the actual patient data, whereas it converged to an unchanged activity when given random data.

In general, the Pearson correlation coefficient is a statistical method that measures the strength and direction of a linear relationship between two given random variables.

The first thing Arkonovich did was teach his Echo to be a Magic 8 Ball and give random "yes", "no" or "maybe" answers to questions he'd ask.

Having in middle age forsaken the other vices (alcohol, cigarettes, meat) of his early life, Mda can't quite conquer his need to give random strangers a ride.

We know that for a given ergodic random process, its autocorrelation function and its power spectral density form a Fourier transform pair, that is,.

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