Sentence examples for model error variance from inspiring English sources

This scheme firstly develops a fixed region model to select the best set of predictor variables for use in the subsequent regression analyses using an approach that minimises the model error variance while also satisfying a number of statistical selection criteria.

An estimator of the approximate out-of-sample model error variance in an estimate of AGB for a tree j with a known (measured) vector x j of explanatory variables is [70, ch.

The model error variance in an estimate of AGB Mg ha−1 for species s is hereafter: (hat{lambda }_{s}^{2} tilde{V}left( {hat{{overline{{text{AGB}_{s} }} }}} right) + left( {hat{{overline{{text{AGB}_{s} }} }}} right)^{2} hat{V}left( {hat{lambda }_{s} } right)) [70, p. 228], if we assume a zero covariance between stem density and AGB.

Under a simple random sampling design, the model error variance in an estimate of a species specific AGB Mg ha−1 in a stratum or a population of interest is obtained by scaling an estimate of the average model error in a tree-level estimates of AGB with an estimate of stem density [40].

Considering the larger contribution to the model error variance from the former, the overestimation is a concern.

An estimator of the approximate out-of-sample model error variance in an estimate of AGB for a tree j with a known (measured) vector x j of explanatory variables is [ 70, ch.

Also, due to the adoption of IK, it can avoid the smoothing effect, remove or lower the unstationary variation of original data by indicator transform, and do not required normal distribution to model the error variance.

The cost function VSNLS in (9) is similar to the cost function V in (6), except that the model prediction error variance λ m is considered in the former, while the sensor measurement error variance σ2 is considered in the latter.

These findings imply that under the model, the error variance was affected significantly by different Harvesters or ELISA operators, respectively.

In this model the error variance for the sentence repetition latent variable was fixed to be equal to the observed error variance on the task at each time point (based on Cronbach's alpha for the sample).

Weights to model the error variance of adjusted means in stage two were computed based on the diagonal elements of the inverse of the asymptotic variance-covariance matrix of adjusted means [ 35].