Sentence examples for more precise random from inspiring English sources

Random slope models will usually include random intercepts, too, so that we prefer the shorthand "random slope model" over the more tedious, though more precise, "random intercept, random slope model".

(Estimation results from corresponding fixed effects models were similar, indicating that endogeneity of the key exposure variables was likely not a problem and thus are not reported in favor of the more precise random effects estimates).

Not only might there be a jammed state that is maximally random--the analogous, but more precise, concept to a random closest packed state--but there might also be some jammed structures that have a very low packing fraction.

We also showed that probability-proportional-to-size sampling of LiDAR strips (utilizing predicted volume from Landsat data as the size variable) led to more precise results than simple random sampling.

They were slightly increased by restricting attention to estimates using a more precise outcome definition, the random-effects estimates changing to 5.59 (5.15-6.07) for the 317 estimates specifically for all lung cancer, 11.56 (9.68-13.81) for the 74 estimates specifically for squamous cell carcinoma, and 2.99 (2.49-3.58) for the 87 estimates specifically for adenocarcinoma.

This gives the GLMM framework a stronger basis for hypothesis testing and for more precise estimates of fixed and random effects.

To be more precise, we use the Monte Carlo random partition to partition the data set into two parts: the training set and the testing set.

In cellular systems, the use of SURS often yields estimates that are more precise than those obtained using simple random sampling and this method of sampling is also easier to carry out.

This angle range can be used to make the generation of random complex weight vector more precise to extend the dynamic range of channel magnitude.

Specifically, the random forest algorithm generated more precise and robust prediction signatures when compared to support vector machines and the more commonly used elastic net regression.

Multi-item scales have more items which increase the scope of a measure; they are less open to variable interpretation; they are more precise and they are more reliable by allowing random errors to average out.