computeTestPartialRegression   package:rotRPackage   R Documentation

_C_o_m_p_u_t_e _t_h_e _P_a_r_t_i_a_l _R_e_g_r_e_s_s_i_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 selection and optionnaly a test level. It then computes
     the result of a regression test against the null hypothesis that
     the selected linear regression coefficients are significant. It
     returns the test result for each selected X variable, the
     statistics and the p-values.

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

     computeTestPartialRegression(outSample, inSample, selection, testLevel = 0.95)

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

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

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

selection: The partial variable selection (vector of column indexes)

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. (vector)

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:

     outSample=iris[1:50,1]
     inSample=as.matrix(iris[1:50,2:4])
     computeTestPartialRegression(outSample, inSample, c(1,2))

