enzyme                 package:VGAM                 R Documentation

_E_n_z_y_m_e _D_a_t_a

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

     Enzyme velocity and substrate concentration.

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

     data(enzyme)

_F_o_r_m_a_t:

     A data frame with 12 observations on the following 2 variables.

     _c_o_n_c a numeric explanatory vector; substrate concentration

     _v_e_l_o_c_i_t_y a numeric response vector; enzyme velocity

_D_e_t_a_i_l_s:

     Sorry, more details need to be included later.

_S_o_u_r_c_e:

     Sorry, more details need to be included later.

_R_e_f_e_r_e_n_c_e_s:

     Watts, D. G. (1981) An introduction to nonlinear least squares.
     In: L. Endrenyi (Ed.), _Kinetic Data Analysis: Design and Analysis
     of Enzyme and Pharmacokinetic Experiments_, pp.1-24. New York:
     Plenum Press.

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

     'micmen'.

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

     data(enzyme)
     fit = vglm(velocity ~ 1, micmen, enzyme, trace = TRUE, crit = "c",
                regressor = enzyme$conc)
     ## Not run: 
     attach(enzyme)
     plot(conc, velocity, xlab="concentration", las=1, main="enzyme data")
     lines(conc, fitted(fit), col="blue")
     detach(enzyme)
     ## End(Not run)

     summary(fit)

