MaxstatTest               package:coin               R Documentation

_M_a_x_i_m_a_l_l_y _S_e_l_e_c_t_e_d _S_t_a_t_i_s_t_i_c_s

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

     Testing the independence of a set of ordered or numeric covariates
     and a response of arbitrary measurement scale against cutpoint
     alternatives.

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

     ## S3 method for class 'formula':
     maxstat_test(formula, data, subset = NULL, weights = NULL, ...)
     ## S3 method for class 'IndependenceProblem':
     maxstat_test(object, 
         distribution = c("asymptotic", "approximate"), 
         teststat = c("maxtype", "quadtype"),
         minprob = 0.1, maxprob = 0.9, ...)

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

 formula: a formula of the form 'y ~ x1 + ... + xp | block' where 'y'
          is a variable measured at arbitrary scale and the covariates
          'x1' to 'xp' are at least of class 'ordered'; 'block' is an
          optional factor for stratification.

    data: an optional data frame containing the variables in the model
          formula.

  subset: an optional vector specifying a subset of observations to be
          used.

 weights: an optional formula of the form '~ w' defining integer valued
          weights for the observations.

  object: an object inheriting from class 'IndependenceProblem'.

distribution: a character, the null distribution of the test statistic
          can be approximated by its asymptotic distribution
          ('asymptotic')  or via Monte-Carlo resampling
          ('approximate'). Alternatively, the functions  'approximate'
          or 'asymptotic' can be used to specify how the exact
          conditional distribution of the test statistic should be
          calculated or approximated.

teststat: a character, the type of test statistic to be applied: a
          maximum type statistic ('maxtype') or a quadratic form
          ('quadform').

 minprob: a fraction between 0 and 0.5;  consider only cutpoints
          greater than  the 'minprob' * 100 % quantile of 'x'.

 maxprob: a fraction between 0.5 and 1;  consider only cutpoints
          smaller than  the 'maxprob' * 100 % quantile of 'x'.

     ...: further arguments to be passed to or from methods.

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

     The null hypothesis of independence of all covariates to the
     response 'y' against simple cutpoint alternatives is tested.

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

     An object inheriting from class 'IndependenceTest-class' with
     methods 'show', 'statistic', 'expectation', 'covariance' and
     'pvalue'. The null distribution can be inspected by 'pperm',
     'dperm',   'qperm' and 'support' methods.

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

     Rupert Miller & David Siegmund (1982), Maximally Selected Chi
     Square Statistics.  _Biometrics_ *38*, 1011-1016.

     Berthold Lausen & Martin Schumacher (1992), Maximally Selected
     Rank Statistics. _Biometrics_ *48*, 73-85.

     Torsten Hothorn & Berthold Lausen (2003), On the Exact
     Distribution of Maximally Selected Rank Statistics. _Computational
     Statistics & Data Analysis_ *43*, 121-137.

     Berthold Lausen, Torsten Hothorn, Frank Bretz & Martin Schumacher
     (2004), Optimally Selected Prognostic Factors. _Biometrical
     Journal_, *46*, 364-374.

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

     data(treepipit, package = "coin")

     maxstat_test(counts ~ coverstorey, data = treepipit)

