SSasympOff               package:stats               R Documentation

_A_s_y_m_p_t_o_t_i_c _R_e_g_r_e_s_s_i_o_n _M_o_d_e_l _w_i_t_h _a_n _O_f_f_s_e_t

_D_e_s_c_r_i_p_t_i_o_n:

     This 'selfStart' model evaluates an alternative parameterization
     of the asymptotic regression function and the gradient with
     respect to those parameters. It has an 'initial' attribute that
     creates initial estimates of the parameters 'Asym', 'lrc', and
     'c0'.

_U_s_a_g_e:

     SSasympOff(input, Asym, lrc, c0)

_A_r_g_u_m_e_n_t_s:

   input: a numeric vector of values at which to evaluate the model.

    Asym: a numeric parameter representing the horizontal asymptote on
          the right side (very large values of 'input').

     lrc: a numeric parameter representing the natural logarithm of the
          rate constant.

      c0: a numeric parameter representing the 'input' for which the
          response is zero.

_V_a_l_u_e:

     a numeric vector of the same length as 'input'.  It is the value
     of the expression 'Asym*(1 - exp(-exp(lrc)*(input - c0)))'.  If
     all of the arguments 'Asym', 'lrc', and 'c0' 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):

     Jose Pinheiro and Douglas Bates

_S_e_e _A_l_s_o:

     'nls', 'selfStart'

_E_x_a_m_p_l_e_s:

     CO2.Qn1 <- CO2[CO2$Plant == "Qn1", ]
     SSasympOff( CO2.Qn1$conc, 32, -4, 43 )  # response only
     Asym <- 32; lrc <- -4; c0 <- 43
     SSasympOff( CO2.Qn1$conc, Asym, lrc, c0 ) # response and gradient
     getInitial(uptake ~ SSasymp( conc, Asym, lrc, c0), data = CO2.Qn1)
     ## Initial values are in fact the converged values
     fm1 <- nls(uptake ~ SSasymp( conc, Asym, lrc, c0), data = CO2.Qn1)
     summary(fm1)

