parwei                package:lmomco                R Documentation

_E_s_t_i_m_a_t_e _t_h_e _P_a_r_a_m_e_t_e_r_s _o_f _t_h_e _W_e_i_b_u_l_l _D_i_s_t_r_i_b_u_t_i_o_n

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

     This function estimates the parameters of the Weibull distribution
     given the L-moments of the data in an L-moment object such as that
     returned by 'lmom.ub'. The Weibull distribution is a reverse
     Generalized Extreme Value distribution.  As result, the
     Generalized Extreme Value algorithms are used for implementation
     of the Weibull in this package. The relation between the
     Generalized Extreme Value parameters (xi, alpha, and kappa) is


                       kappa = 1/delta mbox{,}



                    alpha = beta/delta mbox{, and}



                       xi = zeta - beta mbox{.}


     These relations are taken from Hosking and Wallis (1997).

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

     parwei(lmom)

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

    lmom: A L-moment object created by 'lmom.ub' or 'pwm2lmom'.

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

     An R 'list' is returned.

    type: The type of distribution: 'wei'.

    para: The parameters of the distribution.

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

     W.H. Asquith

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

     Hosking, J.R.M. and Wallis, J.R., 1997, Regional frequency
     analysis-An approach based on L-moments: Cambridge University
     Press.

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

     'lmom.ub', 'lmomwei', 'cdfwei', 'quawei'

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

     lmr <- lmom.ub(rnorm(20))
     parwei(lmr)
     lmr <- parwei(lmom.ub(rweibull(3000,1.3,scale=340)-1200))
     str(lmr)

