

DanielWood(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 ver-
     sus 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 fila-
          ment (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_:

     library(NISTnls)
     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")

