coin                  package:coin                  R Documentation

_G_e_n_e_r_a_l _I_n_f_o_r_m_a_t_i_o_n _o_n _t_h_e _c_o_i_n _P_a_c_k_a_g_e

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

     The 'coin' package implements a general framework for conditional
     inference procedures, commonly known as _permutation tests_,
     theoretically derived by Strasser & Weber (1999). The conditional
     expectation and covariance for a broad class of multivariate
     linear statistics as well as the corresponding multivariate
     limiting distribution was derived by Strasser & Weber (1999).
     These results are  utilized to construct tests for independence
     between two sets of variables. 

     Beside a general implementation of the abstract framework the
     package offers a rather huge set of convenience functions
     implementing well known classical as well as less prominent
     classical and non-classical test procedures  in a conditional
     inference framework. Examples are linear rank statistics for the
     two- and K-sample location and scale problem against ordered and
     unordered alternatives including post-hoc tests for arbitrary
     contrasts, tests of independence for contingency tables, two- and
     K-sample tests for censored data, tests for independence of two
     continuous variables as well as  tests for marginal homogeneity
     and symmetry. Conditional counterparts of  most of the classical
     procedures given in famous text books like Hollander & Wolfe
     (1999) or Agresti (2002) can be implemented as part of the general
     framework without much effort. Approximations of the exact null
     distribution via the limiting distribution and  conditional
     Monte-Carlo procedures are available for every test while the 
     exact null distribution is currently available for two-sample
     problems only.

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

     Helmut Strasser & Christian Weber (1999), On the asymptotic theory
     of permutation statistics.  _Mathematical Methods of Statistics_,
     *8*, 220-250.  

     Myles Hollander & Douglas A. Wolfe (1999),   _Nonparametric
     Statistical Methods, 2nd Edition_. New York: John Wiley & Sons.

     Alan Agresti (2002), _Categorical Data Analysis_. Hoboken, New
     Jersey: John Wiley & Sons.

