

_T_h_e _N_o_n-_C_e_n_t_r_a_l _C_h_i-_S_q_u_a_r_e _D_i_s_t_r_i_b_u_t_i_o_n

     --- these are DEPRECATED, use  Xchisq( . , df, ncp) instead ---

     dnchisq(x, df, lambda)
     pnchisq(q, df, lambda)
     qnchisq(p, df, lambda)
     rnchisq(n, df, lambda)

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

     x,q: vector of quantiles.

       p: vector of probabilities.

       n: number of observations to generate.

df,lambda: degrees of freedom and non-centrality parameter.

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

     - these are DEPRECATED, use  Xchisq( . , df, ncp)
     instead -

     These functions provide information about the non-
     central chi-square distribution with `df' degrees of
     freedom and non-centrality parameter `lambda'.
     `dnchisq' gives the density, `pnchisq' gives the dis-
     tribution function, `qnchisq' gives the quantile func-
     tion and `rnchisq' generates random deviates.

     The non-central chi-square distribution with df degrees
     of freedom and non-centrality parameter lambda has den-
     sity

          f(x) = exp(-lambda/2) SUM_{r=0}^infty (lambda^r / 2^r r!)
          pchisq(x, df + 2r)

     for x >= 0.

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

     `dchisq'.

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

     pnchisq(1, df = 3, lambda = 0) == pchisq(1, df = 3)
     pnchisq(1, df = 3, lambda = 0:4)

