multiecdf            package:geneplotter            R Documentation

_M_u_l_t_i_p_l_e _e_m_p_i_r_i_c_a_l _c_u_m_u_l_a_t_i_v_e _d_i_s_t_r_i_b_u_t_i_o_n _f_u_n_c_t_i_o_n_s (_e_c_d_f)
_a_n_d _d_e_n_s_i_t_i_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     Plot multiple empirical cumulative distribution functions (ecdf)
     and densities with user interface similar to that of 'boxplot'.

_U_s_a_g_e:

     multiecdf(x, ...)
     ## S3 method for class 'formula':
     multiecdf(formula, data = NULL, ..., na.action = NULL)
     ## Default S3 method:
     multiecdf(x, xlim, col, do.points=FALSE, subsample=TRUE, ...)

     multidensity(x, ...)
     ## S3 method for class 'formula':
     multidensity(formula, data = NULL, ..., na.action = NULL)
     ## Default S3 method:
     multidensity(x, xlim, col, ...)

_A_r_g_u_m_e_n_t_s:

 formula: a formula, such as 'y ~ grp', where 'y' is a numeric vector
          of data values to be split into groups according to the
          grouping variable 'grp' (usually a factor).

    data: a data.frame (or list) from which the variables in 'formula'
          should be taken.

na.action: a function which indicates what should happen when the data
          contain 'NA's.  The default is to ignore missing values in
          either the response or the group.

       x: A list of numeric vectors.

    xlim: Range of the x axis.

     col: Line colors. If missing, the 'Set1' palette from RColorBrewer
          is used.

do.points: logical; if 'TRUE', also draw points at the knot locations.

subsample: logical; if 'TRUE', subsamples of size 1000 are used to
          compute and plot the ecdf for list items with many
          observations ('>1000')

     ...: Further arguments that get passed on to the 'plot' functions.

_D_e_t_a_i_l_s:

_V_a_l_u_e:

_A_u_t_h_o_r(_s):

     Wolfgang Huber <URL: http://www.ebi.ac.uk/huber>

_S_e_e _A_l_s_o:

     'boxplot', 'ecdf' 'density'

_E_x_a_m_p_l_e_s:

       f = 1 + (runif(1000)>0.5)
       x = rnorm(length(f), mean=f, sd=f)
       
       multiecdf(x~f)
       multidensity(x~f)

