<p>(<b>A</b>) Standard deviation of the Von Mises component (in blue) from the mixture model fitted to samples of the model shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004003#pcbi.1004003.g008" target="_blank">Fig. 8</a> as a function of the fraction of conjunctive units. The (theoretically-calculated) Fisher information is shown in green for the associated population codes. (<b>B</b>) Mixture proportions of the mixture model fitted on the model samples. This metric is less sensitive to random fluctuations of the samples, and shows that if 50% of the units are conjunctive, then 75% of responses will be correctly associated with the appropriate target angle. (<b>C</b>) P-value for a resampling-based e...
People often overestimate probabilities of conjunctive events. The authors explored whether the accu...
27 pages, 1 article*Bootstrap Confidence Regions Using the Likelihood Ratio Statistic in Mixture Mod...
Summary. We develop a parameterization of the beta-binomial mixture that provides sensible inference...
<p>100 individual samples from the model are generated for specific parameters (<i>M</i> = 200, <i>σ...
<p><b>Left</b>: Memory fidelity based on model samples, while varying the ratio of lower to upper la...
<p>Comparison between similar metrics: the memory fidelity (fitted <i>κ</i>) of single samples colle...
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As mixture regression models increasingly receive attention from both theory and practice, the quest...
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Abstract. We review the history of modeling score distributions, focusing on the mixture of normal-e...
Finite mixtures of probability distributions may be successfully used in the modeling of probability...
<p>The model is capable of recreating error distributions seen in the literature, such as those show...
<p>The graphs quantify different sorts of error in terms of the weights in a mixture model capturing...
We consider mixture models in which the components of data vectors from any given subpopulation are ...
People often overestimate probabilities of conjunctive events. The authors explored whether the accu...
27 pages, 1 article*Bootstrap Confidence Regions Using the Likelihood Ratio Statistic in Mixture Mod...
Summary. We develop a parameterization of the beta-binomial mixture that provides sensible inference...
<p>100 individual samples from the model are generated for specific parameters (<i>M</i> = 200, <i>σ...
<p><b>Left</b>: Memory fidelity based on model samples, while varying the ratio of lower to upper la...
<p>Comparison between similar metrics: the memory fidelity (fitted <i>κ</i>) of single samples colle...
The mixture model likelihood function is invariant with respect to permutation of the components of ...
As mixture regression models increasingly receive attention from both theory and practice, the quest...
Abstract: A common problem in statistical modelling is to distinguish between finite mixture distrib...
We review the history of modeling score distributions, focusing on the mixture of normal-exponential...
Abstract. We review the history of modeling score distributions, focusing on the mixture of normal-e...
Finite mixtures of probability distributions may be successfully used in the modeling of probability...
<p>The model is capable of recreating error distributions seen in the literature, such as those show...
<p>The graphs quantify different sorts of error in terms of the weights in a mixture model capturing...
We consider mixture models in which the components of data vectors from any given subpopulation are ...
People often overestimate probabilities of conjunctive events. The authors explored whether the accu...
27 pages, 1 article*Bootstrap Confidence Regions Using the Likelihood Ratio Statistic in Mixture Mod...
Summary. We develop a parameterization of the beta-binomial mixture that provides sensible inference...