Gaussian Model

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

Colin A. Smith, csmith@scripps.edu

See also

nls, selfStart