SSasympOff                package:nls                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:

     library( nls )
     data( CO2 )
     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)

