pcuseries              package:simecol              R Documentation

_G_e_n_e_r_a_t_e _P_l_a_c_k_e_t_t _B_i_v_a_r_i_a_t_e _R_a_n_d_o_m _N_u_m_b_e_r_s

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

     Generate bivariate uniform random numbers according to the
     Plackett distribution.

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

     pcu(x, alpha = rho2alpha(rho), rho)
     pcuseries(n, alpha = rho2alpha(rho), rho, min = 0, max = 1)
     alpha2rho(alpha)
     rho2alpha(rho)

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

       n: number of observations.

       x: vector of uniformly [0, 1] distributed real numbers.

   alpha: association coefficient of the Plackett distribution.

     rho: Pearson correlation coefficient.

min, max: lower and upper limits of the distribution. Must be finite. 

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

     The functions can be used to generate bivariate distributions with
     uniform marginals. Function 'pcu' generates a vector of uniform
     random values of 'length(x)' which are correlated to the
     corresponding vector 'x', 'pcuseries' generates an auto-correlated
     series, and 'alphatorho' resp. 'rho2alpha' convert between the
     usual correlation coefficient and the association measure of the
     Plackett distribution.

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

     Johnson, M., Wang, C., & Ramberg, J. (1984). Generation of
     multivariate distributions for statistical applications. _American
     Journal of Mathematical and Management Sciences_, *4*, 225-248.

     Nelsen, R. B. (2006). _An Introduction to Copulas_. Springer, New
     York.

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

     'runif'

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

     x <- runif(100)
     y <- pcu(x, rho = 0.8)
     plot(x, y)
     cor(x, y)

     x <- pcuseries(1000, rho=0.8)
     plot(x, type="l")
     acf(x)
     pacf(x)

