eMult                package:occugene                R Documentation

_E_x_p_e_c_t_e_d _V_a_l_u_e _o_f _t_h_e _O_c_c_u_p_a_n_c_y _D_i_s_t_r_i_b_u_t_i_o_n

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

     Returns the expected value of the occupancy distribution based on
     a  multinomial distribution.

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

     eMult(n, p, iter=NULL, seed=NULL, experimental=NULL)

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

       n: number of attempts in the multinomial distribution

       p: probabilities for landing in a specific bin

    iter: number of iterations used in the Monte-Carlo approximation

    seed: seed for the random number generator

experimental: access to other functions of multinomials

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

     This functions computes the expected value of the occupancy
     distribution for a multinomial. In other words, the expected
     number of bins with  at least one ball. The experimental argument
     "oneBall" computes expected number of bins with exactly one ball
     and the experimental argument "nextTo" computes the expected
     number of bins with one ball next to a bin with zero balls.
     Consider any functionality through the experimental  argument
     untested.

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

     Returns a numeric

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

     Oliver Will owill4@yahoo.com

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

     See the book chapter O. Will (**) in ** for specific details about
     this package or Johnson, N. L. and Kotz, S. (1977) _Urn Models and
     Their  Application: An Approach to Modern Discrete Probability
     Theory_.  John Wiley & Sons, New York, NY.

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

     n <- 20
     p <- c(seq(10,1,-1),47)/100
     p <- p/sum(p)
     eMult(n,p)
     eMult(n,p,iter=1000,seed=4)

