plot.qqline               package:sma               R Documentation

_A_d_d _L_i_n_e _G_o_i_n_g _T_h_r_o_u_g_h _t_h_e _Q_u_a_n_t_i_l_e_s _o_f _a _Q-_Q _P_l_o_t

_D_e_s_c_r_i_p_t_i_o_n:

     This function adds a line to a quantile-quantile plot which passes
     through user defined quantiles. This function is similar to, but
     more general than, 'qqline' because the reference distribution
     need not be the standard normal distribution and the quantiles
     need not be the first and third quartiles. 
       Graphical parameters may be given as arguments to 'plot.qqline'.

_U_s_a_g_e:

     plot.qqline(x, y, a=0.25, ...)

_A_r_g_u_m_e_n_t_s:

       x: the reference (first) sample for the Q-Q plot, for a normal
          Q-Q plot this would be the quantiles of a N(0,1) random
          sample.

       y: the data.

       a: a number between 0 and 1. A line is drawn which connects the
          'a' and '1-a' quantile points. The default line passes
          through the first and third quantiles.

     ...: graphical parameters may also be supplied as arguments to the
          function (see 'par').

_S_e_e _A_l_s_o:

     'qqplot', 'qqnorm', 'qqline'.

_E_x_a_m_p_l_e_s:

     data(MouseArray)
     # mouse.setup <- init.grid()
     # mouse.data <- init.data() ## see \emph{init.data}
     # mouse.lratio <- stat.ma(mouse.data, mouse.setup)

     ## Calculation of t-statistics
     ## cl <- c(rep(1,3), rep(2,3))
     ## mouse.t2 <- stat.t2(mouse.lratio, cl)

     ## Diagnostic plots
     plot.qq(mouse.t2$t, "Mouse")

     ## Using the QQline function
     q <- quantile(rnorm(1000))
     plot.qqline(q, mouse.t2$t)

