Lognormal                package:base                R Documentation

_T_h_e _L_o_g _N_o_r_m_a_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, distribution function, quantile function and random
     generation for the log normal distribution whose logarithm has
     mean equal to `meanlog' and standard  deviation equal to `sdlog'.

_U_s_a_g_e:

     dlnorm(x, meanlog = 0, sdlog = 1, log = FALSE)
     plnorm(q, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)
     qlnorm(p, meanlog = 0, sdlog = 1, lower.tail = TRUE, log.p = FALSE)
     rlnorm(n, meanlog = 0, sdlog = 1)

_A_r_g_u_m_e_n_t_s:

    x, q: vector of quantiles.

       p: vector of probabilities.

       n: number of observations to generate.

meanlog, sdlog: mean and standard deviation of the distribution on the
          log scale.

log, log.p: logical; if TRUE, probabilities p are given as log(p).

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

_D_e_t_a_i_l_s:

     If `meanlog' or `sdlog' are not specified they assume the default
     values of `0' and `1' respectively.

     The log normal distribution has density

   f(x) = 1/(sqrt(2 pi) sigma x) e^-((log x - mu)^2 / (2 sigma^2))

     where mu and sigma are the mean and standard deviation of the
     logarithm.

_V_a_l_u_e:

     `dlnorm' gives the density, `plnorm' gives the distribution
     function, `qlnorm' gives the quantile function, and `rlnorm'
     generates random deviates.

_N_o_t_e:

     The cumulative hazard H(t) = - log(1 - F(t)) is `-plnorm(t, r,
     lower = FALSE, log = TRUE)'.

_S_e_e _A_l_s_o:

     `dnorm' for the normal distribution.

_E_x_a_m_p_l_e_s:

     dlnorm(1) == dnorm(0)
     x <- rlnorm(1000)       # not yet always :
     all(abs(x  -  qlnorm(plnorm(x))) < 1e4 * .Machine$double.eps * x)

