SSgauss                 package:xcms                 R Documentation

_G_a_u_s_s_i_a_n _M_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     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'.

_U_s_a_g_e:

     SSgauss(x, mu, sigma, h)

_A_r_g_u_m_e_n_t_s:

       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

_D_e_t_a_i_l_s:

     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)'.

_V_a_l_u_e:

     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'.

_A_u_t_h_o_r(_s):

     Colin A. Smith, csmith@scripps.edu

_S_e_e _A_l_s_o:

     'nls', 'selfStart'

