fitNorm2 {prada} | R Documentation |
Fits a bivariate normal distribution into a data set of paired values and selects data points according to their standard deviation from the fitted distribution.
fitNorm2(x, y=NA, scalefac=1, method="covMcd", noise, gateName = "fitNorm")
x |
Numeric vector containing x-value or n by 2 matrix containing x and
y values or object of class cytoFrame . |
y |
Numeric vector containing y-value (optional). The length of x
must be the same as that of y . |
scalefac |
Numeric vector giving factor of standard deviations
used for data selection (all points within scalefac standard
deviations are selected). |
method |
One of covMcd or cov.rob defining method
used for computation of covariance matrix. |
noise |
Numeric or logical index vector defining value pairs in x that are not used for fitting of distributions. Can be used to deal with noisy data. |
gateName |
Character giving the name of the gate object. |
Computes the densities of a bivariate normal distribution from
the covariance matrix of the paired data. Covariance matrices are
acquired either by function covMcd
(considerably faster) or by function cov.rob
.
A list containing items mu
(midpoint of distribution),
S
(covariance matrix), p
(density values for each
data pair), sel
(selection of data points), scalefac
(factor of standard deviations used for data selection), data
(x and y values of data points) and gate
, an object of class
gate
containing the selection.
Florian Hahne
sampdat <- readFCS(system.file("extdata", "fas-Bcl2-plate323-04-04.A01", package="prada")) nfit <- fitNorm2(exprs(sampdat[,1:2]), scalefac=2) plotNorm2(nfit, selection=TRUE, ellipse=TRUE)