Usage
schechter.ellipse(data, vmax = NA, knee, slope, norm, chi2, datarange = NA, kneerange = c(-24,-16), sloperange = c(-2,1.5), kneeofflims = NA, slopeofflims = NA, kneestep = 0.5, slopestep = 0.1, kneesteps = NA, slopesteps = NA, lim1 = NA, lim2 = NA, numlim = 1, method = "nlminb", volume = max(vmax), bw = 0.1, mag = FALSE, log = FALSE, null = 1E-9, ...)
Arguments
vmax
vector of maximum comoving volumes within which object could lie
knee
the knees(s) of the Schechter function (L_star/M_star)
slope
the slope(s) of the Schechter function (alpha)
norm
the normalisation(s) of the Schechter function (phi_star)
chi2
the full chi2 result from this fit (not reduced)
datarange
the range across which the data is evaluated
kneerange
range of knee values
sloperange
range of slope values
kneeofflims
alternative to kneerange, vector length 2 describing limit offsets from knees
slopeofflims
alternative to sloperange, vector length 2 describing limit offsets from slopes
kneestep
the matrix step in knee values
slopestep
the matrix step in slope values
kneesteps
alternative to kneestep, the number of steps in the matrix
slopesteps
alternative to slopestep, the number of steps in the matrix
lim1
lower data limit for fitting
lim2
upper data limit for fitting
numlim
lower number (per bin) limit for fitting
method
choice of 'nlminb' (recommended) or one of 'optim's minimisation methods (e.g., 'Nelder-Mead')
volume
total volume across which the data has been collected (default 1 if vmax = NA)
mag
are the input data magnitudes?
log
are the input data logged?
...
additional arguments to be passed to 'integrate'