maxKSp                  package:edd                  R Documentation

_c_l_a_s_s_i_f_y _d_e_n_s_i_t_i_e_s _b_y _m_a_x_i_m_u_m _K_S _p-_v_a_l_u_e

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

     compares a sample to reference distributions, identifying the
     closest reference by maximum KS p

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

     maxKSp( x, is.centered=TRUE, dists=eddDistList, thresh=.1 )

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

       x: matrix of samples, distributions to be classified by row 

is.centered: have data been brought to median 0, mad 1 

   dists: list of instances of class eddDist 

  thresh: p-value above which some test must lie, or else 'outlier' is
          declared 

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

     a vector of classifications

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

     X <- rbind( rnorm(30), runif(30), rchisq(30,1))
     tX <- t(apply(X,1,centerScale))
     apply(tX,1,maxKSp)

