DiscreteMVDistribution-class     package:distrEx     R Documentation

_D_i_s_c_r_e_t_e _M_u_l_t_i_v_a_r_i_a_t_e _D_i_s_t_r_i_b_u_t_i_o_n_s

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

     The class of discrete multivariate distributions.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls of the form
     'new("DiscreteMVDistribution", ...)'. More frequently they are
     created via the generating function  'DiscreteMVDistribution'.

_S_l_o_t_s:

     '_i_m_g': Object of class '"rSpace"'.  Image space of the
          distribution. Usually an object of  class '"EuclideanSpace"'.

     '_p_a_r_a_m': Object of class '"OptionalParameter"'. Optional parameter
          of the multivariate distribution.

     '_r': Object of class '"function"':  generates (pseudo-)random
          numbers

     '_d': Object of class '"OptionalFunction"':  optional density
          function

     '_p': Object of class '"OptionalFunction"':  optional cumulative
          distribution function 

     '_q': Object of class '"OptionalFunction"':  optional quantile
          function 

     '_s_u_p_p_o_r_t': numeric matrix whose rows form the support of the
          distribution

_E_x_t_e_n_d_s:

     Class '"MultivariateDistribution"', directly.
      Class '"Distribution"', by class '"MultivariateDistribution"'.

_M_e_t_h_o_d_s:

     _s_u_p_p_o_r_t 'signature(object = "DiscreteMVDistribution")': accessor
          function for slot 'support'.

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

     Matthias Kohl Matthias.Kohl@stamats.de

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

     'Distribution-class', 'MultivariateDistribution-class',
     'DiscreteMVDistribution', 'E-methods'

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

     (D1 <- new("MultivariateDistribution")) # Dirac measure in (0,0)
     r(D1)(5)

     (D2 <- DiscreteMVDistribution(supp = matrix(c(1:5, rep(3, 5)), ncol=2, byrow=TRUE)))
     support(D2)
     r(D2)(10)
     d(D2)(support(D2))
     p(D2)(lower = c(1,1), upper = c(3,3))
     q(D2)
     param(D2)
     img(D2)

     e1 <- E(D2) # expectation

