Sentence examples for recovering estimates from inspiring English sources

The purpose of this Monte Carlo simulation study was to compare the properties of the linear regression model to the more novel beta regression, variable-dispersion beta regression and fractional logit regression models at recovering estimates of average proportion/percentage/rate differences in a two-sample design.

Robust estimates of variance were closer to actual estimates of variance than refitted and recovered estimates.

The relative error in recovered estimates of the residual standard error varied from approximately −20 to +35%%.

Several subsequent analyses using more recent methods have also recovered estimates from within the Permian, 289 and 265 Mya [ 36- 39].

Tabled estimates of the residual standard errors for the three Quercus spp. Were three to four times smaller than recovered estimates.

Hence, the recovered estimates of uncertainty are assumed compatible with estimates that could have been obtained from a sample taken from the population, for which we desire estimates of biomass.

A recovered estimate of the residual variance (see (4)) can be used in a parametric bootstrap [71] to recover a substitute for a missing covariance matrix (text{c} widetilde{text{o}}vleft( {{hat{mathbf{b}}}} right).) The refitting begins with n random draws of residuals (e j *, j = 1, …, n) from a t-distribution with n − q degrees of freedom.

In terms of MC analysis, outlier loci consistently recovered estimated stock proportions that most closely mirrored simulated proportions without exception (Table 3; Table S5).

In general, the linear regression model, the variable-dispersion beta regression model and the fractional logit regression model perform well in terms of recovering unbiased estimates of the non-zero effect measure.

Recovering an estimate of the residual variance was, as expected, easier than recovering a covariance matrix.

A similar pattern is recovered for estimates of known symmetrical extinction values where rates were estimated with more accuracy and precision under low tip bias (asymmetrical speciation rate of 1.25), with accuracy and precision strongly decreasing under high tip bias (20× asymmetry in speciation rates) as observed in Figure  3c.