rvpois                  package:rv                  R Documentation

_G_e_n_e_r_a_t_e _R_a_n_d_o_m _V_e_c_t_o_r_s _f_r_o_m _a _P_o_i_s_s_o_n _S_a_m_p_l_i_n_g _M_o_d_e_l

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

     Generates random variables from a Poisson sampling model.

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

       rvpois(n=1, lambda)

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

       n: integer: number of variables to generate

  lambda: a vector of (positive) mean parameters; (may be random)

_N_o_t_e:

     If any of the arguments are random,  the resulting simulations may
     have non-Poisson marginal distributions.

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

     Jouni Kerman kerman@stat.columbia.edu <URL:
     http://www.stat.columbia.edu/~kerman>

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

     Kerman, Jouni and Gelman, Andrew. Manipulating and Summarizing
     Posterior Simulations Using Random Variable Objects. Technical
     report, Columbia University, New York.

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

       x <- rvpois(lambda=10)  # A Poisson rv with mean 10
       lbd <- rvchisq(1,1)     # Some positive rv
       y <- rvpois(lambda=lbd) # Not a Poisson rv, although each simulation is a draw from Poisson.

