plot.gls package:nlme R Documentation _P_l_o_t _a _g_l_s _O_b_j_e_c_t _D_e_s_c_r_i_p_t_i_o_n: Diagnostic plots for the linear model fit are obtained. The 'form' argument gives considerable flexibility in the type of plot specification. A conditioning expression (on the right side of a '|' operator) always implies that different panels are used for each level of the conditioning factor, according to a Trellis display. If 'form' is a one-sided formula, histograms of the variable on the right hand side of the formula, before a '|' operator, are displayed (the Trellis function 'histogram' is used). If 'form' is two-sided and both its left and right hand side variables are numeric, scatter plots are displayed (the Trellis function 'xyplot' is used). Finally, if 'form' is two-sided and its left had side variable is a factor, box-plots of the right hand side variable by the levels of the left hand side variable are displayed (the Trellis function 'bwplot' is used). _U_s_a_g_e: ## S3 method for class 'gls': plot(x, form, abline, id, idLabels, idResType, grid, ...) _A_r_g_u_m_e_n_t_s: x: an object inheriting from class 'gls', representing a generalized least squares fitted linear model. form: an optional formula specifying the desired type of plot. Any variable present in the original data frame used to obtain 'x' can be referenced. In addition, 'x' itself can be referenced in the formula using the symbol '"."'. Conditional expressions on the right of a '|' operator can be used to define separate panels in a Trellis display. Default is 'resid(., type = "p") ~ fitted(.) ', corresponding to a plot of the standardized residuals versus fitted values, both evaluated at the innermost level of nesting. abline: an optional numeric value, or numeric vector of length two. If given as a single value, a horizontal line will be added to the plot at that coordinate; else, if given as a vector, its values are used as the intercept and slope for a line added to the plot. If missing, no lines are added to the plot. id: an optional numeric value, or one-sided formula. If given as a value, it is used as a significance level for a two-sided outlier test for the standardized residuals. Observations with absolute standardized residuals greater than the 1 - value/2 quantile of the standard normal distribution are identified in the plot using 'idLabels'. If given as a one-sided formula, its right hand side must evaluate to a logical, integer, or character vector which is used to identify observations in the plot. If missing, no observations are identified. idLabels: an optional vector, or one-sided formula. If given as a vector, it is converted to character mode and used to label the observations identified according to 'id'. If given as a one-sided formula, its right hand side must evaluate to a vector which is converted to character mode and used to label the identified observations. Default is the innermost grouping factor. idResType: an optional character string specifying the type of residuals to be used in identifying outliers, when 'id' is a numeric value. If '"pearson"', the standardized residuals (raw residuals divided by the corresponding standard errors) are used; else, if '"normalized"', the normalized residuals (standardized residuals pre-multiplied by the inverse square-root factor of the estimated error correlation matrix) are used. Partial matching of arguments is used, so only the first character needs to be provided. Defaults to '"pearson"'. grid: an optional logical value indicating whether a grid should be added to plot. Default depends on the type of Trellis plot used: if 'xyplot' defaults to 'TRUE', else defaults to 'FALSE'. ...: optional arguments passed to the Trellis plot function. _V_a_l_u_e: a diagnostic 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: 'gls', 'xyplot', 'bwplot', 'histogram' _E_x_a_m_p_l_e_s: fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary, correlation = corAR1(form = ~ 1 | Mare)) # standardized residuals versus fitted values by Mare plot(fm1, resid(., type = "p") ~ fitted(.) | Mare, abline = 0) # box-plots of residuals by Mare plot(fm1, Mare ~ resid(.)) # observed versus fitted values by Mare plot(fm1, follicles ~ fitted(.) | Mare, abline = c(0,1))