

Misra1a(NISTnls)                             R Documentation

_M_o_n_o_m_o_l_e_c_u_l_a_r _A_b_s_o_r_p_t_i_o_n _D_a_t_a

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

     The `Misra1a' data frame has 14 rows and 2 columns.

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

       y: A numeric vector of volume values.

       x: A numeric vector of pressure values.

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

     This data frame contains the following columns:

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

     These data are the result of a NIST study regarding
     dental research in monomolecular adsorption.  The
     response variable is volume, and the predictor variable
     is pressure.

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

     Misra, D., NIST (1978).  Dental Research Monomolecular
     Adsorption Study.

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

     library(NISTnls)
     data(Misra1a)
     plot(y ~ x, data = Misra1a)
     fm1 <- nls(y ~ b1*(1-exp(-b2*x)), data = Misra1a, trace = TRUE,
                start = c(b1 = 500, b2 = 0.0001) )
     fm2 <- nls(y ~ b1*(1-exp(-b2*x)), data = Misra1a, trace = TRUE,
                start = c(b1 = 250, b2 = 0.0005) )
     fm3 <- nls(y ~ 1-exp(-b2*x), data = Misra1a, trace = TRUE,
                start = c(b2 = 0.0001), algorithm = "plinear" )
     fm4 <- nls(y ~ 1-exp(-b2*x), data = Misra1a, trace = TRUE,
                start = c(b2 = 0.0005), algorithm = "plinear" )
     ## Using a self-starting model
     fm5 <- nls(y ~ SSasympOrig(x, Asym, lrc), data = Misra1a)

