| objectiveFunction {ADMUR} | R Documentation | 
Objective function to be minimised in a search. Returns the negative log likelihood.
Description
Calculates the negative log likelihood of a model given a calibrated date matrix.
Usage
objectiveFunction(pars, PDarray, type, taphonomy=FALSE)
Arguments
pars | 
 A numeric vector of parameters.  | 
PDarray | 
 A data frame typically generated by   | 
type | 
 Choose from 'CPL', 'exponential', or 'uniform'.  | 
taphonomy | 
 If TRUE, the last two parameters determine the taphonomic loss rate.  | 
Details
If type is 'CPL', pars must be an odd length each between 0 and 1 since parameters correspond to: (y,x,...y). If type is 'exp', pars must be a single positive or negative numeric (the exponential rate can be growth or decay). Typically this parameter should be close to zero (-0.1 to 0.1) to avoid numbers beyond floating point limits) If type is 'norm', pars must have length 2 (mean and sd) If type is 'uniform', then no parameters are required, and pars must be NULL or c().
Value
Returns a single value, the negative log likelihood.
Examples
	# generate a PD array from a handful of dates
	data <- subset(SAAD, site %in% c('Carrizal','Pacopampa'))
	CalArray <- makeCalArray(shcal13, calrange = c(2000,6000))
	PD <- phaseCalibrator(data, CalArray)
	# the negative log likelihood given some random parameters for a 3-CPL model
	pars <- runif(5)
	objectiveFunction(pars, PD, type='CPL')	
	# the negative log likelihood given a random exponential model
	pars <- runif(1, -0.01, 0.01)
	objectiveFunction(pars, PD, type='exp')	
	# the negative log likelihood given a random Gaussian model
	pars <- c(runif(1, 2000, 6000), runif(1, 100, 1000))
	objectiveFunction(pars, PD, type='norm')	
	# the negative log likelihood given a uniform model
	objectiveFunction(pars=NULL, PD, type='uniform')	
	# the negative log likelihood given a uniform model with taphonomy
	pars <- c(runif(1, 0, 20000), runif(1, -3, 0))
	objectiveFunction(pars=pars, PD, type='uniform', taphonomy=TRUE)