sim.intensity.dep: Simulate Intensity Dependent Variables

In Sage-Bionetworks/snm: Supervised Normalization of Microarrays

Description

This function simulates intensity dependent variables.

Usage

sim.intensity.dep(data = NULL, variable = NULL, spline.dim = NULL, sample.from = NULL, rows = 1)

Arguments

data	The data matrix of simulated data the user wishes to adjust.
variable	The variable the user wishes to introduce.
spline.dim	Dimension of intensity dependent function
sample.from	A list specifying a function that coefficients can be sampled from (e.g. rnorm, rchisq, etc.) and the relevant parameters (e.g. mean, sd, df, etc). The first item in the list should be named func and the second named params.
rows	Either a number between 0 and 1 or a vector of row IDs. A number between 0 and 1 specifies the proportion of data to be influenced by the variable. A vector specifies the rows to be influenced. Equal to 1 by default.

Value

Matrix of dimension equal to that of data containing the intensity-dependent effects.

Author(s)

Brig Mecham <[e-mail]>

Examples

data <- matrix(rchisq(100,1,2),nr=1000,nc=12)
int.var <- data.frame(array=factor(1:12))
array.effect <- sim.intensity.dep(data, int.var$array, 2, list(func=rnorm, params=c(mean=0,sd=0.5)))

Sage-Bionetworks/snm documentation built on May 9, 2019, 12:14 p.m.