dhare               package:polspline               R Documentation

_H_a_r_e: _h_a_z_a_r_d _r_e_g_r_e_s_s_i_o_n

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

     Density ('dhare'), cumulative probability ('phare'), hazard rate
     ('hhare'), quantiles ('qhare'), and  random samples ('rhare') from
      a 'hare' object.

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

     dhare(q, cov, fit) 
     hhare(q, cov, fit) 
     phare(q, cov, fit) 
     qhare(p, cov, fit) 
     rhare(n, cov, fit) 

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

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

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

       n: sample size. If 'length(n)' is larger than 1, then 
          'length(n)' random values are returned.  

     cov: covariates. There are several possibilities. If a vector of
          length  'fit\$ncov' is provided, these covariates are used
          for all elements of 'p' or  'q' or for all random numbers. If
          a matrix of dimension 'length(p)', 'length(q)', or 'n' by
          'fit\$ncov' is provided, the rows of 'cov' are  matched with
          the elements of 'p' or 'q' or every row of 'cov' has its own 
          random number. If a matrix of dimension 'm' times 'fit\$ncov'
          is provided,  while 'length(p) = 1' or 'length(q) = 1' or 'n
          = 1', the single element of 'p' or 'q' is  used 'm' times, or
          'm' random numbers with different sets of covariates are 
          generated.  

     fit: 'hare' object, typically obtained from 'hare'.  

_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.

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

     Densities ('dhare'), hazard rates ('hhare'),  probabilities
     ('phare'), quantiles ('qhare'),  or a random sample ('rhare') from
     a 'hare' object.

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

     Charles Kooperberg clk@fhcrc.org.

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

     Charles Kooperberg, Charles J. Stone and Young K. Truong (1995). 
     Hazard regression.  _Journal of the American Statistical
     Association_, *90*, 78-94.

     Charles J. Stone, Mark Hansen, Charles Kooperberg, and Young K.
     Truong.  The use of polynomial splines and their tensor products
     in extended linear modeling (with discussion) (1997).  _Annals of
     Statistics_, *25*, 1371-1470.

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

     'hare', 'plot.hare', 'summary.hare'.

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

     fit <- hare(testhare[,1], testhare[,2], testhare[,3:8])
     dhare(0:10, testhare[117,3:8], fit)
     hhare(0:10, testhare[1:11,3:8], fit)
     phare(10, testhare[1:25,3:8], fit)
     qhare((1:19)/20, testhare[117,3:8], fit)
     rhare(10, testhare[117,3:8], fit)

