computeLinearModel        package:rotRPackage        R Documentation

_C_o_m_p_u_t_e_s _a _l_i_n_e_a_r _m_o_d_e_l

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

     This ROT function, called from a LinearModelFactory, is given two
     samples  and a confidence level, and is used to compute a linear
     model.  It returns the parameter estimates, confidence intervals
     and p-values.

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

     computeLinearModel(x, y, testLevel = 0.95)

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

       x: A m-by-n matrix containing the explanatory variables.

       y: A n-by-1 vector containng the response variables.

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

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

     A list is returned, containing : 

parameterEstimate: The estimated parameters (vector).

confidenceIntervalLow: The parameters confidence interval lower bounds
          (vector).

confidenceIntervalHigh: The parameters confidence interval lower bounds
          (vector).

 pValues: The parameters p-values.

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

     Pierre-Matthieu Pair, Softia for EDF.

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

     x <- matrix(runif(40), 10, 4)
     r <- matrix(c(1,2,3,4), 4, 1)
     y <- x 
     computeLinearModel(x,y)

