plot.profile.nls package:stats R Documentation _P_l_o_t _a _p_r_o_f_i_l_e._n_l_s _O_b_j_e_c_t _D_e_s_c_r_i_p_t_i_o_n: Displays a series of plots of the profile t function and interpolated confidence intervals for the parameters in a nonlinear regression model that has been fit with 'nls' and profiled with 'profile.nls'. _U_s_a_g_e: ## S3 method for class 'profile.nls': plot(x, levels, conf= c(99, 95, 90, 80, 50)/100, absVal =TRUE, ...) _A_r_g_u_m_e_n_t_s: x: an object of class '"profile.nls"' levels: levels, on the scale of the absolute value of a t statistic, at which to interpolate intervals. Usually 'conf' is used instead of giving 'levels' explicitly. conf: a numeric vector of confidence levels for profile-based confidence intervals on the parameters. Defaults to 'c(0.99, 0.95, 0.90, 0.80, 0.50).' absVal: a logical value indicating whether or not the plots should be on the scale of the absolute value of the profile t. Defaults to 'TRUE'. ...: other arguments to the 'plot' function can be passed here. _A_u_t_h_o_r(_s): Douglas M. Bates and Saikat DebRoy _R_e_f_e_r_e_n_c_e_s: Bates, D.M. and Watts, D.G. (1988), _Nonlinear Regression Analysis and Its Applications_, Wiley (chapter 6) _S_e_e _A_l_s_o: 'nls', 'profile', 'profile.nls' _E_x_a_m_p_l_e_s: require(graphics) # obtain the fitted object fm1 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD) # get the profile for the fitted model pr1 <- profile(fm1, alpha = 0.05) opar <- par(mfrow = c(2,2), oma = c(1.1, 0, 1.1, 0), las = 1) plot(pr1, conf = c(95, 90, 80, 50)/100) plot(pr1, conf = c(95, 90, 80, 50)/100, absVal = FALSE) mtext("Confidence intervals based on the profile sum of squares", side = 3, outer = TRUE) mtext("BOD data - confidence levels of 50%, 80%, 90% and 95%", side = 1, outer = TRUE) par(opar)