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'

