dsurvreg              package:survival              R Documentation

_D_i_s_t_r_i_b_u_t_i_o_n_s _a_v_a_i_l_a_b_l_e _i_n _s_u_r_v_r_e_g.

_D_e_s_c_r_i_p_t_i_o_n:

     Density, cumulative probability, and quantiles for the set of
     distributions supported by the 'survreg' function.

_U_s_a_g_e:

     dsurvreg(x, mean, scale=1, distribution='weibull', parms)
     psurvreg(q, mean, scale=1, distribution='weibull', parms)
     qsurvreg(p, mean, scale=1, distribution='weibull', parms)

_A_r_g_u_m_e_n_t_s:

       x: vector of quantiles.  Missing values ('NA's) are allowed.  

       q: vector of quantiles.  Missing values ('NA's) are allowed.  

       p: vector of probabilities.  Missing values ('NA's) are allowed.            

    mean: vector of means.  This is replicated to be the same length as
          'p'  or 'q'. 

   scale: vector of (positive) scale factors. This is replicated to be
          the same length as 'p'  or 'q'. 

distribution: character string giving the name of the distribution. 
          This must be one of the elements of 'survreg.distributions' 

   parms: optional parameters, if any, of the distribution.  For the
          t-distribution this is the degrees of freedom. 

_D_e_t_a_i_l_s:

     Elements of 'q' or  'p' that are missing will cause the
     corresponding  elements of the result to be missing. 

     The 'mean' and 'scale' values are as they would be for 'survreg'.
     In particular, if the distribution is one that involves a
     transformation, then they are the mean and scale of the
     transformed distribution.   For example, the Weibull distribution
     is fit using the Extreme value distribution along with a log
     transformation. Letting F(t) = 1 - exp(-(at)^p) be the cumulative
     distribution of the Weibull, the mean corresponds to -log(a) and
     the scale to 1/p  (Kalbfleish and Prentice, section 2.2.2).

_V_a_l_u_e:

     density ('dsurvreg'),  probability ('psurvreg'),  quantile
     ('qsurvreg'), or  for the requested distribution with mean and
     scale parameters 'mean' and  'sd'.

_R_e_f_e_r_e_n_c_e_s:

     Kalbfleish, J. D. and Prentice, R. L. (1970).  _The Statistical
     Analysis of Failure Time Data_ Wiley, New York.

_S_e_e _A_l_s_o:

     'survreg',  'Normal'

_E_x_a_m_p_l_e_s:

     # List of distributions available
     names(survreg.distributions)
     ## Not run: 
      [1] "extreme"     "logistic"    "gaussian"    "weibull"     "exponential"
      [6] "rayleigh"    "loggaussian" "lognormal"   "loglogistic" "t"          
     ## End(Not run)
     # Compare results
     all.equal(dsurvreg(1:10, 2, 5, dist='lognormal'), dlnorm(1:10, 2, 5))

     # Hazard function for a Weibull distribution
     x   <- seq(.1, 3, length=30)
     haz <- dsurvreg(x, 2, 3)/ (1-psurvreg(x, 2, 3))
     ## Not run: 
     plot(x, haz, log='xy', ylab="Hazard") #line with slope (1/scale -1)
     ## End(Not run)

