DanielWood              package:NISTnls              R Documentation

_R_a_d_i_a_t_e_d _e_n_e_r_g_y

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

     The `DanielWood' data frame has 6 rows and 2 columns giving the
     energy radiated from a carbon filament versus the absolute
     temperature of the filament.

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

       y: A numeric vector of the energy radiated from a carbon
          filament lamp. 

       x: A numeric vector of the temperature of the filament (1000 K). 

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

     This data frame contains the following columns:

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

     These data and model are described in Daniel and Wood (1980), and
     originally published in E.S.Keeping,  "Introduction to Statistical
     Inference," Van Nostrand Company, Princeton, NJ, 1962, p. 354. 
     The response variable is energy radiated from a carbon filament
     lamp per cm**2 per second, and the predictor variable is the
     absolute temperature of the filament in 1000 degrees Kelvin.

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

     Daniel, C. and F. S. Wood (1980). Fitting Equations to Data,
     Second Edition.  New York, NY:  John Wiley and Sons, pp. 428-431.

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

     data(DanielWood)
     plot(y ~ x, data = DanielWood)
     fm1 <- nls(y ~ b1*x**b2, data = DanielWood, trace = TRUE,
                start = c(b1 = 1, b2 = 5))
     fm2 <- nls(y ~ b1*x**b2, data = DanielWood, trace = TRUE,
                start = c(b1 = 0.7, b2 = 4))
     fm3 <- nls(y ~ x**b2, data = DanielWood, trace = TRUE,
                start = c(b2 = 5), algorithm = "plinear")
     fm4 <- nls(y ~ x**b2, data = DanielWood, trace = TRUE,
                start = c(b2 = 4), algorithm = "plinear")

