distplot                 package:vcd                 R Documentation

_D_i_a_g_n_o_s_t_i_c _D_i_s_t_r_i_b_u_t_i_o_n _P_l_o_t_s

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

     Diagnostic distribution plots: poissonness, binomialness and
     negative binomialness plots.

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

     distplot(x, type = c("poisson", "binomial", "nbinomial"),
       size = NULL, lambda = NULL, legend = TRUE, xlim = NULL, ylim = NULL,
       conf_int = TRUE, conf_level = 0.95, main = NULL,
       xlab = "Number of occurrences", ylab = "Distribution metameter",
       gp = gpar(cex = 0.5), name = "distplot", newpage = TRUE, pop = TRUE, ...)

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

       x: either a vector of counts, a 1-way table of frequencies of
          counts or a data frame or matrix with frequencies in the
          first column and the corresponding counts in the second
          column.

    type: a character string indicating the distribution.

    size: the size argument for the binomial and negative binomial
          distribution. If set to 'NULL' and 'type' is '"binomial"',
          then 'size' is taken to be the maximum count.  If set to
          'NULL' and 'type' is '"nbinomial"', then 'size' is estimated
          from the data.

  lambda: parameter of the poisson distribution. If type is '"poisson"'
          and 'lambda' is specified a leveled poissonness plot is
          produced.

  legend: logical.  Should a legend be plotted?

    xlim: limits for the x axis.

    ylim: limits for the y axis.

conf_int: logical.  Should confidence intervals be plotted?

conf_level: confidence level for confidence intervals.

    main: a title for the plot.

    xlab: a label for the x axis.

    ylab: a label for the y axis.

      gp: a '"gpar"' object controlling the grid graphical parameters
          of the points.

    name: name of the plotting viewport.

 newpage: logical. Should 'grid.newpage' be called  before plotting?

     pop: logical. Should the viewport created be popped?

     ...: further arguments passed to 'grid.points'.

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

     'distplot' plots the number of occurrences (counts) against the
     distribution metameter of the specified distribution.  If the
     distribution fits the data, the plot should show a straight line.
     See Friendly (2000) for details.

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

     Achim Zeileis Achim.Zeileis@R-project.org

_R_e_f_e_r_e_n_c_e_s:

     D. C. Hoaglin (1980), A poissonness plot, _The American
     Statistican_, *34*, 146-149.

     D. C. Hoaglin & J. W. Tukey (1985), Checking the shape of discrete
     distributions. In D. C. Hoaglin, F. Mosteller, J. W. Tukey (eds.),
     _Exploring Data Tables, Trends and Shapes_, chapter 9. John Wiley
     & Sons, New York.

     M. Friendly (2000), _Visualizing Categorical Data_. SAS Institute,
     Cary, NC.

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

     ## Simulated data examples:
     dummy <- rnbinom(1000, size = 1.5, prob = 0.8)
     distplot(dummy, type = "nbinomial")

     ## Real data examples:
     data("HorseKicks")
     data("Federalist")
     data("Saxony")
     distplot(HorseKicks, type = "poisson")
     distplot(HorseKicks, type = "poisson", lambda = 0.61)
     distplot(Federalist, type = "poisson")
     distplot(Federalist, type = "nbinomial", size = 1)
     distplot(Federalist, type = "nbinomial")
     distplot(Saxony, type = "binomial", size = 12)

