Skip to content

bivariate normal distribution

Cut-off BVN limited to an ellipsoidal core

Covariance matrix of a cut-off Multivariate Normal Distribution – III – results for a 2-dimensional BVN-core and proper normalization of its cut-off distribution

In the math section of this blog, we try to cover interesting aspects of Multivariate Normal Distributions [MVNs]. The topic of this post series is the covariance matrix of a MVN-like distribution confined inside a hyper-surface of constant probability density. Outside of the surface we set the probability density to zero. This gives us a “cut-off” MVN- distribution. Contour surfaces… Read More »Covariance matrix of a cut-off Multivariate Normal Distribution – III – results for a 2-dimensional BVN-core and proper normalization of its cut-off distribution

Iterative method to compute the covariance-matrix of MVN-like inner cores of multivariate distributions with strongly asymmetric outer layers – I

In other posts in this blog (see [1] to [3]), I have discussed multiple methods to calculate and construct confidence ellipses of “Bivariate Normal Distributions” [BVNs]. BVNs are the marginal distributions of “Multivariate Normal Distributions” [MVNs] in e.g. n dimensions ( n > 2). Therefore, two-dimensional confidence ellipses appear as projections of n-dimensional concentric confidence ellipsoids of MVNs onto (2-dim) coordinate planes. The properties of the confidence ellipsoids, which also give us contours of the probability density, are defined by the variance-covariance matrix Σ of the MVN. This post discusses a method to compute the confidence ellipsoids and ellipses for an inner MVN-like core of an otherwise largely asymmetric distribution, which in its overall shape and structure deviates strongly from a MVN.

Read More »Iterative method to compute the covariance-matrix of MVN-like inner cores of multivariate distributions with strongly asymmetric outer layers – I

How to compute confidence ellipses – III – 4 alternative construction methods

In previous mathematical posts of this blog, we have studied some core properties of Bivariate Normal Distributions [BVDs]. During the rather mathematical tour de force we have come across various methods to construct and plot confidence ellipses for a given confidence level and respective Mahalanobis distance from the distribution’s center. We have also covered the mathematical derivation of the methods.… Read More »How to compute confidence ellipses – III – 4 alternative construction methods

How to compute confidence ellipses – II – equivalence of Schelp’s basic construction method for confidence ellipse with other approaches

In the 1st post of this series, I have motivated a simple method for constructing confidence ellipses for assumedly Bivariate Normal Distributions [BVD] or at least approximate BVDs. A reader has asked me, whether one can prove more rigidly that the proposed method of C. Schelp is equivalent to other BVD-based methods. Well, in this post we show that the… Read More »How to compute confidence ellipses – II – equivalence of Schelp’s basic construction method for confidence ellipse with other approaches