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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| finance× 81 | computational-statistics× 80 | naive-bayes× 80 |
jags× 79
Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS." (http://mcmc-jags.sourcefo…
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discrete-data× 79
Refers to data generated from a distribution that has a countable sample space. Discrete data may be nominal (e.g. the distribution of race in a sample of individuals) or ordinal (e.g. the number of e…
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prior× 79 |
power× 79
Is a property of a hypothesis testing method: the probability of rejecting the null hypothesis given that it is false. The power of a test depends on sample size, effect size, and the significance ($\…
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ranking× 76 |
| causal-inference× 76 | median× 76 |
r-squared× 75
In linear regression, the coefficient of determination, usually symbolized by $R^2$, is the proportion of the total response variance explained by the regression model.
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post-hoc× 73
decided upon after the data has been collected, as opposed to "a priori".
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| genetics× 73 |
information-theory× 72
determine the information carrying capacity of a channel, whether one that is used for communication or one that is defined in an abstract sense. Entropy is…
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stationarity× 72 |
uniform× 71
The uniform distribution describes a random variable that is equally likely to take any value in its sample space. A discrete random variable that is uniformly distributed on a set of outcome $\{1, 2,…
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bias× 70
Bias, in a statistical framework, means that an estimate of a parameter has an expected value that is not equal to the actual parameter value. There is often a tradeoff between bias and variance - low…
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distance-functions× 70 | entropy× 69 | basic-concepts× 69 |
| continuous-data× 69 |
kolmogorov-smirnov× 69
a test for goodness of fit of data to a distribution. It is often used to test whether a variable is normally distributed.
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negative-binomial× 69
A discrete random variable $X$ has a negative binomial distribution, indexed by parameters $p \in (0,1)$ and $r \in \mathbb{Z}$ if its probability mass function is
$$ \Pr(X = k) = {k+r-1 \choose k…
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unbiased-estimator× 69
Refers to an estimator of a population parameter that "hits the true value" on average. That is, a function of the observed data $\hat{\theta}$ is an unbiased estimator of a parameter $\theta$ if $E(\…
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longitudinal× 68
collected repeatedly on the same subjects. When there is a long series of data, time series analysis may be appropriate. For shorter series, mixed models (a…
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autoregressive× 68 |
bugs× 68
an acronym for Bayesian inference Using Gibbs Sampling; BUGS is also a software package for doing this.
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signal-processing× 67
Numerical analysis of a digitized signal
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standardization× 66
Shifting and rescaling data to assure zero mean and unit variance.
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average× 66
Average most often refers to the arithmetic mean, but more generally to measures of central tendency that use most, or all, of the data values. Examples include trimmed mean, Winsorized mean, harmonic…
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fisher× 66 |
gamma-distribution× 64
A non-negative continuous probability distribution indexed by two strictly positive parameters.
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| measurement-error× 64 | group-differences× 63 | fixed-effects-model× 63 | smoothing× 63 |
