

SSasympOff {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 parame-
     terization 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 loga-
          rithm 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 gra-
     dient 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)

