Sentence examples for bootstrap parameters can be from inspiring English sources

In this case, the bootstrap parameters can be used to construct a family of curves representing the likely range of concentrations for patients with a given set of covariates.

Alternatively, prediction ability (of gene expression and unknown parameters) can be assessed using some empirical method (cross-validation or bootstrap), assuming that data replicates are available.

Any of the parameters can be changed above.

Both Monte Carlo and bootstrap methods can be applied in Excel spreadsheets to resample a large number of measurements for dependent variable from which different values of parameters can be obtained.

That parameter can be set to "users" or "followings".

Since each tree in Random Forest is trained on a bootstrap subset of the parameters, these can be used to estimate the importance of a parameter by calculating the decrease in classification accuracy when the parameter is omitted from a model.

More general methods such as Monte Carlo and bootstrap simulation can be used to estimate the parameter uncertainties.

Our results clearly show that the Monte Carlo and bootstrap methods can be used to estimate the parameter uncertainties using spreadsheet methods.

For empirical datasets collected from natural populations, bootstrap replicates can be used to approximate confidence intervals around parameter estimates [ 4], and modifications to AIC can help correct for biases in model selection [ 31].

Further, with little modification, the Monte Carlo method or bootstrap method can be used in Microsoft Excel to estimate the uncertainty of hydrologic or environmental predictions with single or multiple input parameters under different degrees of uncertainty.

Alternatively, a bootstrap approach can be followed.