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I calculate the standard error on the marginal effect estimated at the mean using a parametric bootstrap with 1,000 repetitions.
Uncertainty in model parameters was quantified using confidence intervals obtained through bootstrapping the data, and uncertainty in model outputs such as the predicted degree distribution was quantified using a parametric bootstrap.
nfidence intervals for τwere calculated using a parametric bootstrap approach [82].
Standard errors were calculated for the MLE method using a parametric bootstrap.
The significance of the difference in likelihood scores was evaluated using a parametric bootstrap in which 1000 data matrices of 400 bases (the size of the final dataset excluded sites where any individuals had unknown bases) were simulated using the HKY model in Mesquite [75].
We tested the validity of the estimated stepwise expansion model using a parametric bootstrap approach.
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Following Gumedze et al. [ 6], we use a parametric bootstrap procedure to obtain the distributions of the LRT statistics (5).
We used a parametric bootstrap for the link between the amount of energy consumed and body mass, assuming a normal distribution.
To evaluate the significance of the VMRs, we used a parametric bootstrapping approach.
To estimate the probability of transcripts appearing to be bimodally expressed due to chance alone we used a parametric bootstrapping method.
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.
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using a unified bootstrap
using a parametric algorithm
using a parametric investigation
using a rapid bootstrap
using a parametric description
using a parametric face
using a parametric cylinder
using a parametric scheme
using a residual bootstrap
using a different bootstrap
using a parametric mediation
using a parametric task
using a null bootstrap
using a parametric amplifier
using a validated bootstrap
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