rweibull                 package:evd                 R Documentation

_T_h_e _R_e_v_e_r_s_e_d _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:

     Density function, distribution function, quantile function and
     random generation for the reversed Weibull distribution with
     location, scale and shape parameters.

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

     drweibull(x, loc=0, scale=1, shape=1, log = FALSE) 
     prweibull(q, loc=0, scale=1, shape=1, lower.tail = TRUE) 
     qrweibull(p, loc=0, scale=1, shape=1, lower.tail = TRUE)
     rrweibull(n, loc=0, scale=1, shape=1)

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

    x, q: Vector of quantiles.

       p: Vector of probabilities.

       n: Number of observations.

loc, scale, shape: Location, scale and shape parameters (can be given
          as vectors).

     log: Logical; if 'TRUE', the log density is returned.

lower.tail: Logical; if 'TRUE' (default), probabilities are P[X <= x],
          otherwise, P[X > x]

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

     The reversed Weibull distribution function with parameters 'loc' =
     a, 'scale' = b and 'shape' = s is

                      G(x) = exp{-[-(z-a)/b]^s}

     for z < a and one otherwise, where b > 0 and s > 0.

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

     'drweibull' gives the density function, 'prweibull' gives the
     distribution function, 'qrweibull' gives the quantile function,
     and 'rrweibull' generates random deviates.

_N_o_t_e:

     Within extreme value theory the reversed Weibull distibution is
     usually referred to as the Weibull distribution. I make a
     distinction to avoid confusion with the three-parameter
     distribution used in survival analysis, which is related by a
     change of sign to the distribution given above.

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

     'rfrechet', 'rgev', 'rgumbel'

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

     drweibull(-5:-3, -1, 0.5, 0.8)
     prweibull(-5:-3, -1, 0.5, 0.8)
     qrweibull(seq(0.9, 0.6, -0.1), 2, 0.5, 0.8)
     rrweibull(6, -1, 0.5, 0.8)
     p <- (1:9)/10
     prweibull(qrweibull(p, -1, 2, 0.8), -1, 2, 0.8)
     ## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

