fitNorm2 {prada} | R Documentation

## Fit bivariate normal distribution.

### Description

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.

### Usage

    fitNorm2(x, y=NA, scalefac=1, method="covMcd", noise, gateName = "fitNorm")

### Arguments

`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.

### Details

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`.

### Value

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.

### Author(s)

Florian Hahne

### See Also

`cov.rob`, `covMcd`, `plotNorm2`

### Examples

     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)

[Package prada version 1.10.1 Index]