partial.mahalanobis | R Documentation |
Computes the partial square Mahalanobis distance for all observations in x. Let \mathbf{x} = (x_{i1},...,x_{ip})' be a p-dimensional random vector and \mathbf{u} = (u_{i1},...,u_{ip})' be a p-dimensional vectors of zeros and ones indicating which entry is missing: 0 as missing and 1 as observed. Then partial mahalanobis distance is given by:
d(\mathbf{x, u, m, Σ}) = (\mathbf{x^{(u)}} - \mathbf{m^{(u)}})' (\mathbf{Σ^{(u)}})^{-1}(\mathbf{x^{(u)}} - \mathbf{m^{(u)}}).
With no missing data, this function is equivalent to mahalanobis distance.
partial.mahalanobis(x, mu, Sigma)
x |
a matrix or data frame. May contain missing values, but cannot contain columns with completely missing entries. |
mu |
location estimate |
Sigma |
scatter estimate. Must be positive definite |
An S4 object of class CovRobMiss-class
.
The output S4 object contains the following slots:
mu | Estimated location. Can be accessed via getLocation . |
S | Estimated scatter matrix. Can be accessed via getScatter . |
pmd | Squared partial Mahalanobis distances. Can be accessed via getDist . |
pmd.adj | Adjusted squared partial Mahalanobis distances. Can be accessed via getDistAdj . |
pu | Dimension of the observed entries for each case. Can be accessed via getDim . |
call | Object of class "language" . Not meant to be accessed. |
x | Input data matrix. Not meant to be accessed. |
p | Column dimension of input data matrix. Not meant to be accessed. |
estimator | Character string of the name of the estimator used. Not meant to be accessed. |
Andy Leung andy.leung@stat.ubc.ca
## Not run: ## suppose we would like to compute pmd for an MLE x <- matrix(rnorm(1000),100,10) U <- matrix(rbinom(1000,1,0.1),100,10) x <- x * ifelse(U==1,NA,1) ## compute MLE (i.e. EM in this case) res <- CovEM(x) ## compute pmd res.pmd <- partial.mahalanobis(x, mu=getLocation(res), S=getScatter(res)) summary(res.pmd) plot(res.pmd, which="index") ## End(Not run)
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