liesInSupport            package:distrEx            R Documentation

_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _T_e_s_t_i_n_g _t_h_e _S_u_p_p_o_r_t _o_f _a _D_i_s_t_r_i_b_u_t_i_o_n

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

     The function tests if 'x' lies in the support of the distribution
     'object'.

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

     liesInSupport(object, x)

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

  object: object of class '"Distribution"' 

       x: numeric vector or matrix 

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

     logical vector

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

     _o_b_j_e_c_t = "_D_i_s_c_r_e_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _x = "_n_u_m_e_r_i_c": does 'x' lie in
          the support of 'object'. 

     _o_b_j_e_c_t = "_D_i_s_c_r_e_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _x = "_m_a_t_r_i_x": does 'x' lie in the
          support of 'object'. 

     _o_b_j_e_c_t = "_A_b_s_c_o_n_t_D_i_s_t_r_i_b_u_t_i_o_n", _x = "_n_u_m_e_r_i_c": does 'x' lie in the
          support of 'object'. 

     _o_b_j_e_c_t = "_A_b_s_c_o_n_t_D_i_s_t_r_i_b_u_t_i_o_n", _x = "_m_a_t_r_i_x": does 'x' lie in the
          support of 'object'. 

     _o_b_j_e_c_t = "_D_i_s_c_r_e_t_e_M_V_D_i_s_t_r_i_b_u_t_i_o_n", _x = "_n_u_m_e_r_i_c": does 'x' lie in
          the support of 'object'. 

     _o_b_j_e_c_t = "_D_i_s_c_r_e_t_e_M_V_D_i_s_t_r_i_b_u_t_i_o_n", _x = "_m_a_t_r_i_x": does 'x' lie in
          the support of 'object'. 

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

     Matthias Kohl Matthias.Kohl@stamats.de

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

     'Distribution-class'

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

     liesInSupport(Exp(1), rnorm(10))

     # note
     x <- rpois(10, lam = 10)
     liesInSupport(Pois(1), x)
     # better
     distroptions("TruncQuantile"=1e-15)
     liesInSupport(Pois(1), x)
     distroptions("TruncQuantile"=1e-05) # default

     M <- matrix(rpois(30, lam = 10), ncol = 3)
     D1 <- DiscreteMVDistribution(M)
     M1 <- rbind(r(D1)(10), matrix(rpois(30, lam = 10), ncol = 3))
     liesInSupport(D1, M1)

