Summarize a matrix of simulations by their mean (median), sd (mad), and quantiles
Utility function to summarize the output from ‘simulate’ functions in this package
summary_simulate(object, probs = c(0.025, 0.975), robust = FALSE, ...)
object |
nobs x nsim matrix where nobs are the number of observations in the dataset and nsim are the number of simulations |
probs |
the percentiles to be computed by the quantile function |
robust |
If FALSE (the default) the mean is used as the measure of central tendency and the standard deviation as the measure of variability. If TRUE, the median and the median absolute deviation (MAD) are applied instead. |
... |
additional arguments to be passed. (none used at the moment) |
data(barley, package = "nlraa") fit <- nls(yield ~ SSlinp(NF, a, b, xs), data = barley) sim <- simulate_nls(fit, nsim = 100) sims <- summary_simulate(sim)
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