Discrete                package:e1071                R Documentation

_D_i_s_c_r_e_t_e _D_i_s_t_r_i_b_u_t_i_o_n

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

     These functions provide information about the discrete
     distribution where the probability of the elements of `values' is
     proportional to the values given in `probs', which are normalized
     to sum up to 1. `ddiscrete' gives the density, `pdiscrete' gives
     the distribution function, `qdiscrete' gives the quantile function
     and `rdiscrete' generates random deviates.

     For the generation of the random deviates, one can choose between
     the method "inverse" which basically makes a lookup in the vector
     of the probabilities and the method "alias". The later method
     computes an aliasmatrix by the function `aliasmat' which allows a
     faster data generation once this matrix is computed. If such a
     matrix has already been computed, it can be passed as further
     argument to `rdiscrete'.

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

     ddiscrete(x, probs, values=1:length(probs))
     pdiscrete(q, probs, values=1:length(probs))
     qdiscrete(p, probs, values=1:length(probs))
     rdiscrete(n, probs, values=1:length(probs), method="inverse", aliasmatrix=NULL)
     aliasmat(p)

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

     x,q: vector or array of quantiles.

       p: vector or array of probabilites.

       n: number of observations.

   probs: probabilities of the distribution.

  values: values of the distribution.

  method: generation method, can be "inverse" or "alias"

aliasmatrix: matrix needed by alias method

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

     Andreas Weingessel and Friedrich Leisch

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

     # a vector of length 30 whose elements are 1 with probability 0.2 and 2
     # with probability 0.8.
     rdiscrete (30, c(0.2, 0.8))

     # a vector of length 100 whose elements are A, B, C, D.
     # The probabilities of the four values have the relation 1:2:3:3
     rdiscrete (100, c(1,2,3,3), c("A","B","C","D"))

