Sentence examples for models we employed from inspiring English sources

To compare and evaluate different pre-processing techniques and models, we employed a cross-validation approach.

To compare the reward and salience prediction error models, we employed a design that delivered both appetitive (monetary) and aversive (noise burst) outcomes.

To construct realistic inhomogeneous crustal models, we employed stochastic random elastic fluctuations characterized by an exponential-type power spectral density function in the wavenumber domain (β = 2 of the von Kármán-type power spectral density function).

Due to the characteristics of the different cell models, we employed different methods to assess viability and apoptosis.

To minimize sample set bias and to aid in the assessment of intermediate models, we employed one-third "out-of-bag" (OOB) error estimation and an external 100-fold bootstrap validation with 10% holdout bootstraps.

To reassess our models we employed standard regression models using robust standard errors.

To be able to use the explicit mathematical description of these models, we employ the Finite Cell Method (FCM).

To complement the presentation of the estimated coefficients for the logistic regression models, we employ a statistic, D, the coefficient of determination (Tjur 2008).

Section 2 describes the two related statistical models we employ.

Unlike some dedicated provider models, we employ MSI staff, not external providers.

To address the lower dimensional variables of these models, we employ an empirical Bayes approach.