x-displacement distributions for six different lag times Δ = {3, 6, 15, 30, 60, 120} mins, where δx = x(t + Δ) − x(t) for all time points t ∈ [0, T − Δ] where T is the length of the track. Cells included in this analysis have track lengths greater than or equal to 120 mins. Maximum likelihood fits for both a generalized Gaussian distribution (red line) and a standard Gaussian distribution (broken black line) are shown. The shape parameter γ for the generalized Gaussian fit is shown along with the lag time Δ in the top left of each plot.</p
<p>The plot describes the data fit by three different distributions. The Gaussian distribution does ...
This contribution deals with Monte Carlo simulation techniques for generalized Gaussian random varia...
Abstract—We consider covariance estimation in themultivariate generalized Gaussian distribution (MGG...
Reproduction of Fig 7 for the simulated data. As in Fig 7 we show x-displacement distributions for s...
The non-Gaussianity parameter G(Δ) shown for lag-times of up to one hour. At short times the departu...
<p>Panels (a), (b) and (c) are respectively the displacement distributions generated by the present ...
<p>(A) Distribution of intervals produced by the timing network for (top), (middle) and (bottom)....
Displacement probability distribution P(ρ), where ρ(t) is the scaled displacement , for the value of...
Most estimators of the shape parameter of generalized Gaussian distribution (GGD) assume asymptotic ...
<p>Each horizontal line corresponds to a different dataset. Lines extend from the minimum Δ<i>r</i> ...
<p>Yellow dotted line: data. Black dashed line: Log-normal fit with characteristic parameter <i>μ</i...
<p>Green dotted line: data. Black dashed line: Log-normal fit with characteristic parameter <i>μ</i>...
The normal inverse Gaussian (NIG) and generalized asymmetric Laplace (GAL) distributions can be seen...
<p><b>A</b>) The distribution of DOWN state durations inferred by the HMM algorithm for an example L...
<p>Probability density functions (PDF) of Gaussian (<b>a</b>) and mean (<b>b</b>) curvatures. Like b...
<p>The plot describes the data fit by three different distributions. The Gaussian distribution does ...
This contribution deals with Monte Carlo simulation techniques for generalized Gaussian random varia...
Abstract—We consider covariance estimation in themultivariate generalized Gaussian distribution (MGG...
Reproduction of Fig 7 for the simulated data. As in Fig 7 we show x-displacement distributions for s...
The non-Gaussianity parameter G(Δ) shown for lag-times of up to one hour. At short times the departu...
<p>Panels (a), (b) and (c) are respectively the displacement distributions generated by the present ...
<p>(A) Distribution of intervals produced by the timing network for (top), (middle) and (bottom)....
Displacement probability distribution P(ρ), where ρ(t) is the scaled displacement , for the value of...
Most estimators of the shape parameter of generalized Gaussian distribution (GGD) assume asymptotic ...
<p>Each horizontal line corresponds to a different dataset. Lines extend from the minimum Δ<i>r</i> ...
<p>Yellow dotted line: data. Black dashed line: Log-normal fit with characteristic parameter <i>μ</i...
<p>Green dotted line: data. Black dashed line: Log-normal fit with characteristic parameter <i>μ</i>...
The normal inverse Gaussian (NIG) and generalized asymmetric Laplace (GAL) distributions can be seen...
<p><b>A</b>) The distribution of DOWN state durations inferred by the HMM algorithm for an example L...
<p>Probability density functions (PDF) of Gaussian (<b>a</b>) and mean (<b>b</b>) curvatures. Like b...
<p>The plot describes the data fit by three different distributions. The Gaussian distribution does ...
This contribution deals with Monte Carlo simulation techniques for generalized Gaussian random varia...
Abstract—We consider covariance estimation in themultivariate generalized Gaussian distribution (MGG...