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A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.

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a regression technique from econometrics used in instrumental variables analysis.
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For questions asking about the meaning of abbreviations that are widely used in statistics.
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used in problems when the likelihood function is intractable by producing datasets that are sufficiently similar to the observed dataset
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a synonym for incidence. This is a "measure of the rate at which people without a disease develop it during a specific period of time"
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A/B testing, also known as split or bucket testing, is a controlled comparison of the effectiveness of variants of a website, email, or other commercial product.
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The community pursuing research, education or scholarship, typically although not universally in universities.
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for accept-reject sampling methods. These are also known as rejection sampling methods. These methods sample a random variable from a dominating measure (h) and accepts the draw if an aux…
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the degree of closeness of the estimates to the true value. For a classifier, accuracy is the proportion of correct classifications. (This second usage is not good practice…
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The AutoCorrelation Function and Partial AutoCorrelation Function pertain to the correlation of a time series with itself at different lags. They are used to detect non-independence & suggest p, d, q …
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a setting where an automated learning system can request labels from an external source, perhaps a human user or a real-world experiment. It is used to try to learn good models whil…
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Questions relating to financial risk; often, but not limited to, insurance. This includes questions regarding stochastic distribution of cash flows, probability of ruin, financial payments above a thr…
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A popular boosting algorithm (short for "adaptive boosting"). Boosting combines weakly predictive models into a strongly predictive model.
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AdaGrad (for adaptive gradient algorithm) is an enhanced stochastic gradient descent algorithm that automatically determines a per-parameter learning rate.
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An adaptive algorithm for gradient-based optimization of stochastic objective functions, often used to train deep neural networks.
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Refers to "lumping together" potentially inhomogeneous groups of data.
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the degree to which two raters, instruments, etc, give the same value when applied to the same object. Special statistical methods have been designed for this task.
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AIC stands for the Akaike Information Criterion, which is one technique used to select the best model from a class of models using a penalized likelihood. A smaller AIC implies a better model.
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Use for questions relating to algebraic statistics, the branch of statistical theory concerned with methods from abstract algebra, especially algebraic geometry and commutative algebra. This tag is no…
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An unambiguous list of computational steps involved in finding a solution to a class of problems.
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IBM SPSS AMOS, proprietary structural equation modelling software.
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For questions dealing with the applied analysis of a specific dataset or design of experiment. Posts tagged analysis are requesting statistical consulting assistance from the network. Questions tagged…