SSgauss: Gaussian Model
In xcms: LC-MS and GC-MS Data Analysis

Description Usage Arguments Details Value Author(s) See Also

This selfStart model evalueates the Gaussian model and its gradient. It has an initial attribute that will evalueate the inital estimates of the parameters mu, sigma, and h.

1	SSgauss(x, mu, sigma, h)

`x`	a numeric vector of values at which to evaluate the model
`mu`	mean of the distribution function
`sigma`	standard deviation of the distribution fuction
`h`	height of the distribution function

Initial values for mu and h are chosen from the maximal value of x. The initial value for sigma is determined from the area under x divided by h*sqrt(2*pi).

A numeric vector of the same length as x. It is the value of the expression h*exp(-(x-mu)^2/(2*sigma^2), which is a modified gaussian function where the maximum height is treated as a separate parameter not dependent on sigma. If arguments mu, sigma, and h are names of objects, the gradient matrix with respect to these names is attached as an attribute named gradient.

Colin A. Smith, csmith@scripps.edu

nls, selfStart

xcms documentation built on Nov. 8, 2020, 5:13 p.m.