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Everything about Probability mass function
Discrete-variable probability distribution
In probability and statistics, a probability mass function (PMF), discrete probability density function, probability function, or frequency function is a function that gives the probability that a discrete random variable is exactly equal to some value. The PMF is often the primary means of defining a discrete probability distribution, and such functions exist for either scalar or multivariate random variables whose domain is discrete. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Probability mass functionA 5-minute orientation
- Skim a recent paper: Sample regeneration algorithm for structural failure probability function estimationInfluential work since 2022
- Pick up a classic book: Information-Theoretic Methods for Estimating of Complicated Probability Distributions, Volume 207 (Mathematics in Science and Engineering)The most-reprinted book on the subject
- Read the landmark paper: On Estimation of a Probability Density Function and ModeCited 8,422 times
- Go sideways: Random variableA closely related topic
- Go sideways: Random elementA closely related topic
📖 Definitions
Noun A function that gives the relative probability that a discrete random variable is exactly equal to some value.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
On Estimation of a Probability Density Function and Mode
Probability transformation of mass function: A weighted network method based on the ordered visibility graph
Multi-objective tabu search using a multinomial probability mass function
Discrete triangular distributions and non-parametric estimation for probability mass function
Stabilized GAN models training with kernel-histogram transformation and probability mass function distance
Probability distribution function of the aperture mass field with large deviation theory
Maximum Likelihood Set for Estimating a Probability Mass Function
Fractal-based basic probability assignment: A transient mass function
🆕 Influential since 2022
Sample regeneration algorithm for structural failure probability function estimation
Response probability density function for non-bijective transformations
Hierarchical importance sampling method for estimating failure probability function
Asymptotic properties of the normalised discrete associated-kernel estimator for probability mass function
Influence factor-based transformation method for translating mass function to probability in Dempster–Shafer evidence theory
📚 Books worth reading
Information-Theoretic Methods for Estimating of Complicated Probability Distributions, Volume 207 (Mathematics in Science and Engineering)Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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