schechter.ellipse: Calculate Error Matrices for a Schechter Function Fit
In astro: Astronomy Functions, Tools and Routines

Description Usage Arguments Value Author(s) See Also

This function calculates ellipsoidal error matrices for a given Schechter Function fit.

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, ...)

`data`	input data vector
`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)
`bw`	bin width sizes
`mag`	are the input data magnitudes?
`log`	are the input data logged?
`null`	value of null
`...`	additional arguments to be passed to 'integrate'

`knees`	knee bin midpoints
`slopes`	slope bin midpoints
`res1`	result matrix for knee1/slope1
`res2`	result matrix for knee2/slope2
`s1`	1 sigma chi2 limit (min+2.30)
`s2`	2 sigma chi2 limit (min+6.17)
`s3`	3 sigma chi2 limit (min+11.8)
`kneelo1`	lower knee error (all sigmas)
`kneehi1`	upper knee error (all sigmas)
`slopelo1`	lower slope error (all sigmas)
`slopehi1`	upper slope error (all sigmas)
`kneelo2`	lower secondary knee error (all sigmas)
`kneehi2`	upper secondary knee error (all sigmas)
`slopelo2`	lower secondary slope error (all sigmas)
`slopehi2`	upper secondary slope error (all sigmas)