plot.Variogram package:nlme R Documentation _P_l_o_t _a _V_a_r_i_o_g_r_a_m _O_b_j_e_c_t _D_e_s_c_r_i_p_t_i_o_n: an 'xyplot' of the semi-variogram versus the distances is produced. If 'smooth = TRUE', a 'loess' smoother is added to the plot. If 'showModel = TRUE' and 'x' includes an '"modelVariog"' attribute, the corresponding semi-variogram is added to the plot. _U_s_a_g_e: ## S3 method for class 'Variogram': plot(x, smooth, showModel, sigma, span, xlab, ylab, type, ylim, grid, ...) _A_r_g_u_m_e_n_t_s: x: an object inheriting from class 'Variogram', consisting of a data frame with two columns named 'variog' and 'dist', representing the semi-variogram values and the corresponding distances. smooth: an optional logical value controlling whether a 'loess' smoother should be added to the plot. Defaults to 'TRUE', when 'showModel' is 'FALSE'. showModel: an optional logical value controlling whether the semi-variogram corresponding to an '"modelVariog"' attribute of 'x', if any is present, should be added to the plot. Defaults to 'TRUE', when the '"modelVariog"' attribute is present. sigma: an optional numeric value used as the height of a horizontal line displayed in the plot. Can be used to represent the process standard deviation. Default is 'NULL', implying that no horizontal line is drawn. span: an optional numeric value with the smoothing parameter for the 'loess' fit. Default is 0.6. xlab,ylab: optional character strings with the x- and y-axis labels. Default respectively to '"Distance"' and '"SemiVariogram"'. type: an optional character indicating the type of plot. Defaults to '"p"'. ylim: an optional numeric vector with the limits for the y-axis. Defaults to 'c(0, max(x$variog))'. grid: an optional logical value indicating whether a grid should be added to plot. Default is 'FALSE'. ...: optional arguments passed to the Trellis 'xyplot' function. _V_a_l_u_e: an 'xyplot' Trellis plot. _A_u_t_h_o_r(_s): Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu _S_e_e _A_l_s_o: 'Variogram', 'xyplot', 'loess' _E_x_a_m_p_l_e_s: fm1 <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary) plot(Variogram(fm1, form = ~ Time | Mare, maxDist = 0.7))