computeTestPartialPearson    package:rotRPackage    R Documentation

_C_o_m_p_u_t_e _t_h_e _P_a_r_t_i_a_l _P_e_a_r_s_o_n _T_e_s_t _o_n _2 _d_a_t_a _s_e_t_s.

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

     This ROT function, called from a Test C++ object, is given 2
     samples, a vector specifying which variables are to be tested, and
     optionnaly  a test level. It then returns the result of a PP test
     against the  null hypothesis that the in/out variables are not
     correlated, and  the test p-values.

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

     computeTestPartialPearson(inData, outData, selection, testLevel = 0.95)

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

  inData: The 'in' sample. (m-by-n matrix)

 outData: The 'out' sample (n vector).

selection: The list of partial tests (vector containing the  indexes of
          the variables to be tested.

testLevel: the test level. (scalar in [0:1])

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

     A list is returned, containing : 

testResult: The result. 1 means H0 is not rejected. (scalar)

threshold: The threshold applied to the p-value when deciding the
          outcome of the test.

 pvalues: The test pvalues. (vector)

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

     Pierre-Matthieu Pair, Softia for EDF.

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

     outData=runif(4)
     inData=matrix(runif(40), 4, 10)
     selection=c(1,2,3,6,9)
     computeTestPartialPearson(inData,outData,selection)

