qnormp                package:normalp                R Documentation

_Q_u_a_n_t_i_l_e_s _o_f _a_n _e_x_p_o_n_e_n_t_i_a_l _p_o_w_e_r _d_i_s_t_r_i_b_u_t_i_o_n

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

     Quantiles for the exponential power distribution with location
     parameter 'mu', scale parameter 'sigmap' and shape parameter 'p'.

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

     qnormp(pr, mu=0, sigmap=1, p=2, lower.tail=TRUE, log.pr=FALSE)

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

      pr: Vector of probabilities.

      mu: Vector of location parameters.

  sigmap: Vector of scale parameters.

       p: Shape parameter.

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

  log.pr: Logical; if TRUE, probabilities pr are given as log(pr).

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

     If 'mu', 'sigmap' or 'p' are not specified they assume the default
     values 0, 1 and 2, respectively. The exponential power
     distribution has density function


 f(x) = 1/(2 p^(1/p) Gamma(1+1/p) sigmap) exp{-|x - mu|^p/(p sigmap^p)}


     where mu is the location parameter, sigmap the scale parameter and
     p the shape parameter. When p=2 the exponential power distribution
     becomes the Normal Distribution, when p=1 the exponential power
     distribution becomes the Laplace Distribution, when p->infinity
     the exponential power distribution becomes the Uniform
     Distribution.

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

     'qnormp' gives the quantiles of an exponential power distribution.

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

     Angelo M. Mineo

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

     'Normal' for the Normal distribution, 'Uniform' for the Uniform
     distribution, and 'Special' for the Gamma function.

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

     ## Compute the quantiles for a vector of probabilities x
     ## with mu=1, sigmap=2 and p=1.5
     x <- 0.3
     q <- qnormp(x, 1, 2, 1.5)
     q

