vsn: vsnLikelihood – R documentation

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vsnLikelihood

Calculate the log likelihood and its gradient for the vsn model

Description

logLik calculates the log likelihood and its gradient for the vsn model. plotVsnLogLik makes a false color plot for a 2D section of the likelihood landscape.

Usage

## S4 method for signature 'vsnInput'
logLik(object, p, mu = numeric(0), sigsq=as.numeric(NA), calib="affine")

plotVsnLogLik(object,
              p,
              whichp = 1:2,
              expand = 1,
              ngrid = 31L,
              fun = logLik,
              main = "log likelihood",
              ...)

Arguments

`object`	A `vsnInput` object.
`p`	For `plotVsnLogLik`, a vector or a 3D array with the point in parameter space around which to plot the likelihood. For `logLik`, a matrix whose columns are the set of parameters at which the likelihoods are to be evaluated.
`mu`	Numeric vector of length 0 or `nrow(object)`. If the length is 0, there is no reference and `sigsq` must be `NA` (the default value). See `vsn2`.
`sigsq`	Numeric scalar.
`calib`	as in `vsn2`.
`whichp`	Numeric vector of length 2, with the indices of those two parameters in `p` along which the section is to be taken.
`expand`	Numeric vector of length 1 or 2 with expansion factors for the plot range. The range is auto-calculated using a heuristic, but manual adjustment can be useful; see example.
`ngrid`	Integer scalar, the grid size.
`fun`	Function to use for log-likelihood calculation. This parameter is exposed only for testing purposes.
`main`	This parameter is passed on `levelplot`.
`...`	Arguments that get passed on to `fun`, use this for `mu`, `sigsq`, `calib`.

Details

logLik is an R interface to the likelihood computations in vsn (which are done in C).

Value

For logLik, a numeric matrix of size nrow(p)+1 by ncol(p). Its columns correspond to the columns of p. Its first row are the likelihood values, its rows 2...nrow(p)+1 contain the gradients. If mu and sigsq are specified, the ordinary negative log likelihood is calculated using these parameters as given. If they are not specified, the profile negative log likelihood is calculated.

For plotVsnLogLik, a dataframe with the 2D grid coordinates and log likelihood values.

Author(s)

Wolfgang Huber

Examples

data("kidney")

v = new("vsnInput", x=exprs(kidney),
  pstart=array(as.numeric(NA), dim=c(1, ncol(kidney), 2)))
 
fit = vsn2(kidney)
print(coef(fit))

p = sapply(seq(-1, 1, length=31), function(f) coef(fit)+c(0,0,f,0))

ll = logLik(v, p)

plot(p[3, ], ll[1, ], type="l", xlab=expression(b[1]), ylab=expression(-log(L)))
abline(v=coef(fit)[3], col="red")

plotVsnLogLik(v, coef(fit), whichp=c(1,3), expand=0.2)

vsn

Variance stabilization and calibration for microarray data

v3.58.0

Artistic-2.0

Authors

Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth

Initial release