csimint               package:multcomp               R Documentation

_S_i_m_u_l_t_a_n_e_o_u_s _C_o_n_f_i_d_e_n_c_e _I_n_t_e_r_v_a_l_s _B_a_s_e_d _o_n _P_a_r_a_m_e_t_e_r _E_s_t_i_m_a_t_e_s

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

     Computes simultaneous intervals for several multiple procedures
     based on precomputed parameter estimates.

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

     csimint(estpar, df, covm, cmatrix = NULL, 
             ctype = "user-defined", conf.level = 0.95, 
             alternative = c("two.sided", "less", "greater"),
             asympt = FALSE, eps = 0.001, maxpts = 1e+06)

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

  estpar: estimated parameter vector. 

      df: degrees of freedom. 

    covm: estimated covariance matrix of 'estpar'. 

 cmatrix: contrast matrix. 

   ctype: a string decribing the kind of contrast matrix used. Only
          used for printing in 'print.hmtest'. 

conf.level: confidence level. 

alternative: the alternative hypothesis must be one of '"two.sided"'
          (default), '"greater"' or '"less"'.  You can specify just the
          initial letter. 

  asympt: a logical indicating whether the (exact) t-distribution or
          the normal approximation should be used.

     eps: absolute error tolerance as double.

  maxpts: maximum number of function values as integer.

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

     This is the work-horse for 'simint'. If only parameter estimates
     and estimates of the (co)variances are available, simultaneous
     confidence intervals can be computed with this low-level function.
     See 'cholesterol' for an example.

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

     an object of class 'hmtest'

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

     Frank Bretz <bretz@ifgb.uni-hannover.de> and  
       Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>

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

     Frank Bretz, Alan Genz and Ludwig A. Hothorn (2001), On the
     numerical  availability of multiple comparison procedures.
     _Biometrical Journal_, *43*(5), 645-656.

