Calibration plots for asymptotic (A,B), and bootstrap (C,D) confidence intervals of the duration and rate of exponential growth for Scenario 1 with t1 = 100 gens and r1 = 6.4% per gen for 200 simulated data sets of 10,000 diploids, each with 100 unlinked loci of length m. For each confidence level α on the x-axis, the y-axis counts the fraction of data sets where the true parameter estimates lie outside the 100(1 − α)% predicted confidence interval. The straight black lines denote the plot that would be obtained from an idealized confidence interval estimation procedure. (A,B) Asymptotic confidence interval calibration plots for the inferred (A) duration and (B) rate of exponential growth. As the locus length m increases, linkage disequilibrium causes the composite log-likelihood approximation in Equation 9 to become increasingly inaccurate, thus leading to poorly calibrated asymptotic confidence intervals for m = 10 kb. (C,D) Bootstrap confidence interval calibration plots using 200 bootstrap replicates per simulated data set for the inferred (C) duration and (D) rate of exponential growth. The bootstrap confidence intervals are much better calibrated than those produced by the asymptotic confidence interval estimation procedure.
