<p>From left to right: kernels with the minimum, lower quartile, median, upper quartile and maximum Kullback-Leibler (KL) distances (posterior mean), as estimated (red) under the most exhaustive scheme (Θ<sub>4</sub>), based on simulated epidemics with short-, medium- and long-range kernels (from top to bottom; black). Kernels are represented by their marginal cumulative distribution function <i>F</i><sup>1<i>D</i></sup> (with distance from the source represented on the log<sub>10</sub> scale). The mean KL distance is indicated for each estimation.</p
1. Seed dispersal is a key biological process that remains poorly documented because dispersing seed...
Calculates mean for random samples of 6 individuals per status in each array. Fits linear mixed mode...
<p>Error bars show standard deviations. <i>ne</i> denotes the four nearest neighbor dispersal, <i>gl...
<p><b>A–D</b> Estimated kernels for the exponential model (orange lines) and the Cauchy model (cyan ...
<p>A comparison of the A) distance pdf and B) density with respect to distance for estimates using M...
<p>A) Maximum likelihood estimate density with respect to distance for Malaysian data. B) Maximum li...
<p>(A–B) Mean dispersal ability: During the invasion, the dispersal ability at the front is higher t...
<p>Examples of different kernel interpretations for the negative exponential (A, B and C) and expone...
Calculates mean, standard deviation, skew, kurtosis, and maximum for random samples of 6 individuals...
The dispersal kernel plays a fundamental role in stochastic spatiotemporal epidemic models. By quant...
<p>The posterior marginal cumulative distribution function, <i>F</i><sup>1<i>D</i></sup>, of the fit...
Calculates standard deviation and maximum for random samples of 6 individuals per status in each arr...
<p>δ<sub>s</sub> = 0.20 (plain line), δ<sub>s</sub> = 1.00 (dashed line) and δ<sub>s</sub> = 3.54 ( ...
<p>(<b>A</b>) A symmetric, two–dimensional probability density function (dispersal kernel). Dispersa...
<p>Simulated (gray line) and observed (colored histograms) dispersal values for full-sibling, aunt/u...
1. Seed dispersal is a key biological process that remains poorly documented because dispersing seed...
Calculates mean for random samples of 6 individuals per status in each array. Fits linear mixed mode...
<p>Error bars show standard deviations. <i>ne</i> denotes the four nearest neighbor dispersal, <i>gl...
<p><b>A–D</b> Estimated kernels for the exponential model (orange lines) and the Cauchy model (cyan ...
<p>A comparison of the A) distance pdf and B) density with respect to distance for estimates using M...
<p>A) Maximum likelihood estimate density with respect to distance for Malaysian data. B) Maximum li...
<p>(A–B) Mean dispersal ability: During the invasion, the dispersal ability at the front is higher t...
<p>Examples of different kernel interpretations for the negative exponential (A, B and C) and expone...
Calculates mean, standard deviation, skew, kurtosis, and maximum for random samples of 6 individuals...
The dispersal kernel plays a fundamental role in stochastic spatiotemporal epidemic models. By quant...
<p>The posterior marginal cumulative distribution function, <i>F</i><sup>1<i>D</i></sup>, of the fit...
Calculates standard deviation and maximum for random samples of 6 individuals per status in each arr...
<p>δ<sub>s</sub> = 0.20 (plain line), δ<sub>s</sub> = 1.00 (dashed line) and δ<sub>s</sub> = 3.54 ( ...
<p>(<b>A</b>) A symmetric, two–dimensional probability density function (dispersal kernel). Dispersa...
<p>Simulated (gray line) and observed (colored histograms) dispersal values for full-sibling, aunt/u...
1. Seed dispersal is a key biological process that remains poorly documented because dispersing seed...
Calculates mean for random samples of 6 individuals per status in each array. Fits linear mixed mode...
<p>Error bars show standard deviations. <i>ne</i> denotes the four nearest neighbor dispersal, <i>gl...