Davies                package:Davies                R Documentation

_T_h_e _D_a_v_i_e_s _d_i_s_t_r_i_b_u_t_i_o_n

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

     Density, distribution function, quantile function and random
     generation for the Davies distribution

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

      ddavies(x, params)
      pdavies(x, params)
      qdavies(p, params)
      rdavies(n, params)
     ddavies.p(x,params)

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

       x: quantile

       p: vector of probabilities

       n: number of observations.  If 'length(n) > 1', the length is
          taken to be the number required

  params: A three-member vector holding~C , lambda1 and~lambda2

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

     The Davies distribution is defined in terms of its quantile
     function:

                      Cp^lambda_1/(1-p)^lambda2


     It does not have a closed-form  probability density function or
     cumulative density function, so numerical solution is used.

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

     'ddavies' gives the density, 'pdavies' gives the distribution
     function, 'qdavies' gives the quantile function, and 'rdavies'
     generates random deviates.

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

     Robin K. S. Hankin

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

     draft MS available from the author on request

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

     'Gld', 'fit.davies.p', 'least.squares', 'skewness'

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

     params <- c(10,0.1,0.1)
     x <- seq(from=4,to=20,by=0.2)
     p <- seq(from=1e-3,to=1-1e-3,len=50)

     rdavies(n=5,params)
     least.squares(rdavies(100,params))
     plot(pdavies(x,params))

     plot(p,qdavies(p,params))
     plot(x,ddavies(x,params),type="b")

