gpuQr                package:gputools                R Documentation

_E_s_t_i_m_a_t_e _t_h_e _Q_R _d_e_c_o_m_p_o_s_i_t_i_o_n _f_o_r _a _m_a_t_r_i_x

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

     This function estimates the QR decomposition for a matrix using
     column pivoting and householder matricies.  The work is done on a
     GPU.

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

     gpuQr(a)

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

       a: a matrix of floating point numbers.  This is the matrix that
          will be decomposed into Q and R factors.

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

     a list consisting of the following elements:  Q, R, pivot, rank. Q
     is a matrix representing the Q factor of input a.  R is a matrix
     representing the upper triangular R factor of input a.  The pivot
     element is a vector representing the final permutation of the
     columns of a after the QR decomposition function finishes
     decomposing a.  The format of pivot is similar to the base R
     function 'qr'.  The rank element is a single integer representing
     an estimation of the rank of input matrix 'a' based on the results
     of the QR decomposition.  In some rare cases, this rank can be
     wildly different from the actual rank of the matrix a.  It is only
     an estimation.

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

     Bjorck, Ake (1996) _Numerical methods for least squares problems_.
     SIAM.

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

             # get some random data of any shape at all
             x <- matrix(runif(1000), 50, 20)
             qr <- gpuQr(x)
             print(qr)

