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Bivariate normal distribution

For means

μ_{i}

, standard deviations

σ_{i}

, and correlation

ρ

, the standardized quadratic form in the density is

\frac{1}{1 - ρ ^{2}} [\frac{( x _{1} - μ _{1} ) ^{2}}{σ _{1}^{2}} - \frac{2 ρ ( x _{1} - μ _{1} ) ( x _{2} - μ _{2} )}{σ _{1} σ _{2}} + \frac{( x _{2} - μ _{2} ) ^{2}}{σ _{2}^{2}}] .

Table of contents 62 3
- Maximum-likelihood covariance estimator for centered Gaussian data Bivariate normal distribution 28 1
  - Asymptotic covariance of the bivariate Gaussian covariance estimator Maximum-likelihood covariance estimator for centered Gaussian data 19
- Conditional distribution of a bivariate normal variable Bivariate normal distribution 8

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