SSgauss: Gaussian Model

In sneumann/xcms: LC-MS and GC-MS Data Analysis

Gaussian Model

Description

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.

Usage

SSgauss(x, mu, sigma, h)

Arguments

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

Details

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).

Value

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.

Author(s)

Colin A. Smith, [e-mail]

See Also

nls, selfStart

sneumann/xcms documentation built on Nov. 23, 2024, 6:53 p.m.