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The time between the arrival of one point & the next, as in a point process or queue. More abstractly, 'time' can be a distance between 2 points in a space.
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when there is less variability than there 'ought' to be in the data. Eg, the variance of counts could be less than the mean, whereas the variance of a Poisson should equal the mean.
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an algorithm by Laurens van der Maaten and Geoffrey Hinton published in 2008 in the Journal of Machine Learning Research, 9, with the title "Visualizing Data using t-SNE". t-SNE is a dimensio…
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a transformation that is applied to the correlation coefficient, r, for use in hypothesis testing & constructing confidence intervals.
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Geographic information systems (GIS) provide facilities for storing, managing and analyzing geographic data which can be used for statistical purposes.
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an R package to fit generalized additive mixed models using mgcv (mixed GAM computation vehicle) and lme4 (linear mixed-effects models).
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used to assess the accuracy of predicted probabilities, or more generally of predictive densities. Examples of scoring rules include the logarithmic, Brier, spherical, ranked probabi…
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Sandwich, or sandwich variance estimation, refers to a method of estimating standard errors from estimating equations that is robust to many model based assumptions.
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used to model the relation between individual location (ability) on a latent trait and their probability of endorsing a dichotomous item, which is characterized by its difficulty, a…
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a high-quality typesetting system and is available as free software.
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Manifold learning subsumes techniques conceived for problems where data of interest are assumed to lie on an embedded non-linear manifold within a higher-dimensional space.
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A non-negative continuous probability distribution characterized by one strictly positive parameter.
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