Distribution of items for participants in the Gaussian and Uniform conditions in Experiment 1. To ease visualization, we normalized each participant’s values. (A) We calculated the average proportion of values of each participant in each of thirty bins, so that each participant had equal weight in the resulting plot. Comparing the aggregate histograms shows that in the uniform condition participants had a flatter distribution. (B) Shape measure of each participant for the Gaussian and Uniform conditions, with the dashed line representing equal values for both conditions. Error bars are 95% confidence intervals (obtained via bootstrapping). Most participants had a more Gaussian sequence in the Gaussian condition (participants below the dashe...
Assessing the distributional assumptions about univariate and multivariate data is a basic concern i...
A randomization test based on scaled factorial moments was developed to identify and determine the s...
This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gau...
<p>Conceptual plot shows theoretical feature (OTU 1) abundance distributions for control samples and...
<p><b>(A)</b> Responses (black) show higher consistency with inference of a single Gaussian than wit...
<p>a–c) Histograms (bars) of sample stimulus sets from each condition with average probability densi...
Background: Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatt...
<p><b>a,</b> Probability distribution of the 512 possible 3×3 1-bit pixel patterns (grey histogram)....
<p>A) Quantization stability: variation of the average SSIntra among 270 LOO subsets. The black dot ...
This Mathematica demonstration compares the sample uniform probability distribution with the theoret...
<p>Panel a shows the means of the original distributions for and in blue and red, respectively. In...
Unlike in Fig 1, for better clarity these results are actually displayed on a logarithmic scale. The...
<p>(<b>A</b>) The difference in the true-positive rate TP<sub>N</sub>–TP<sub>U</sub> represents the ...
<p>Each panel shows the (unnormalized) probability density for a ‘prior’ distribution of targets, gr...
<p>Each row shows examples of probability densities (black lines) for a different sample (green and ...
Assessing the distributional assumptions about univariate and multivariate data is a basic concern i...
A randomization test based on scaled factorial moments was developed to identify and determine the s...
This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gau...
<p>Conceptual plot shows theoretical feature (OTU 1) abundance distributions for control samples and...
<p><b>(A)</b> Responses (black) show higher consistency with inference of a single Gaussian than wit...
<p>a–c) Histograms (bars) of sample stimulus sets from each condition with average probability densi...
Background: Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatt...
<p><b>a,</b> Probability distribution of the 512 possible 3×3 1-bit pixel patterns (grey histogram)....
<p>A) Quantization stability: variation of the average SSIntra among 270 LOO subsets. The black dot ...
This Mathematica demonstration compares the sample uniform probability distribution with the theoret...
<p>Panel a shows the means of the original distributions for and in blue and red, respectively. In...
Unlike in Fig 1, for better clarity these results are actually displayed on a logarithmic scale. The...
<p>(<b>A</b>) The difference in the true-positive rate TP<sub>N</sub>–TP<sub>U</sub> represents the ...
<p>Each panel shows the (unnormalized) probability density for a ‘prior’ distribution of targets, gr...
<p>Each row shows examples of probability densities (black lines) for a different sample (green and ...
Assessing the distributional assumptions about univariate and multivariate data is a basic concern i...
A randomization test based on scaled factorial moments was developed to identify and determine the s...
This dissertation develops a new figure of merit to measure the similarity (or dissimilarity) of Gau...