qqnorm.gls               package:nlme               R Documentation

_N_o_r_m_a_l _P_l_o_t _o_f _R_e_s_i_d_u_a_l_s _f_r_o_m _a _g_l_s _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     Diagnostic plots for assessing the normality of residuals the
     generalized least squares 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.

_U_s_a_g_e:

     ## S3 method for class 'gls':
     qqnorm(y, form, abline, id, idLabels, grid, ...)

_A_r_g_u_m_e_n_t_s:

       y: an object inheriting from class 'gls', representing a
          generalized least squares fitted model.

    form: an optional one-sided formula specifying the desired type of
          plot. Any variable present in the original data frame used to
          obtain 'y' can be referenced. In addition, 'y' 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. The expression
          on the right hand side of 'form' and to the left of a '|'
          operator must evaluate to a residuals vector. Default is '~
          resid(., type = "p")',  corresponding to a normal plot of the
          standardized residuals.

  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 (random effects).
          Observations with absolute standardized residuals (random
          effects) 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 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 and used to label the
          identified observations. Default is the innermost grouping
          factor.

    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 for assessing normality of residuals.

_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', 'plot.gls'

_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))
     qqnorm(fm1, abline = c(0,1))