Everything about Multivariate normal distribution
Generalization of the one-dimensional normal distribution to higher dimensions
In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. One definition is that a random vector is said to be k-variate normally distributed if every linear combination of its k components has a univariate normal distribution. Its importance derives mainly from the multivariate central limit theorem. The multivariate normal distribution is often used to describe, at least approximately, any set of (possibly) correlated real-valued random variables, each of which clusters around a mean value. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Multivariate normal distributionA 5-minute orientation
- Skim a recent paper: A comprehensive comparison of copula models and multivariate normal distribution for geo-material parametric dataInfluential work since 2022
- Pick up a classic book: Models for repeated measurementsThe most-reprinted book on the subject
- Read the landmark paper: The multivariate skew-normal distributionCited 1,283 times
- Go sideways: Covariance matrixA closely related topic
- Go sideways: Central limit theoremA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
The multivariate skew-normal distribution
Statistical Applications of the Multivariate Skew Normal Distribution
The Skew-normal Distribution and Related Multivariate Families*
The multivariate Poisson-log normal distribution
The multivariate complex normal distribution-a generalization
Some results on the multivariate truncated normal distribution
A multivariate skew normal distribution
The multivariate distribution of complex normal variables
🆕 Influential since 2022
A comprehensive comparison of copula models and multivariate normal distribution for geo-material parametric data
Effect of Normal Transformation Methods on Performance of Multivariate Normal Distribution
A multivariate modified skew-normal distribution
Bayesian Wavelet Stein’s Unbiased Risk Estimation of Multivariate Normal Distribution Under Reflected Normal Loss
An EM algorithm for estimating the parameters of the multivariate skew-normal distribution with censored responses
📚 Books worth reading
Models for repeated measurementsJames K. Lindsey · 1993
The multivariate normal distributionYung Liang Tong · 1990
Distributions of Test StatisticsA. M. Mathai · 1990
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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