Calculate the log likelihood and its gradient for the vsn model

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 class '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.

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.

Details

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

Author

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))
#> , , 1
#> 
#>            [,1]       [,2]
#> [1,] -0.5504617 -0.5350711
#> 
#> , , 2
#> 
#>           [,1]      [,2]
#> [1,] -5.835777 -5.861253
#> 

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)