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Calculating probability contours using qmvnorm

The inverse problem to the calculation of cumulative probability is as follows: for a given a probability \(p\) calculate the contour that contains \(p\) proportion of the total volume of the density. This contour is the same as the \(p^{th}\) quantile of the distribution. The qmvnorm() function provides the tools to perform the above calculations.

Cet exercice fait partie du cours

Multivariate Probability Distributions in R

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Instructions

  • Compute the contour for a standard bivariate normal which contains probability \(p=0.9\).
  • Calculate the contour for a bivariate normal with mean mu.sim and variance-covariance matrix sigma.sim which contains probability \(p=0.95\).

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Probability contours for a standard bivariate normal
qmvnorm(___, tail = "both", sigma = diag(2))

# Probability contours for a bivariate normal 
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