MVR                package:clim.pact                R Documentation

_M_u_l_t_i_v_a_r_i_a_t_e _r_e_g_r_e_s_s_i_o_n _a_n_a_l_y_s_i_s

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

     Applies a multivariate regression (MVR) analysis to two data sets.
     The MVR here is based on the projection to obtain a least squares
     approximation and uses the formula of  Strang (1988) "Linear
     Algebra and its applications", Harcourt Brace and Company, p. 156.
      The method is also documented in Benestad (1999) "MVR applied to
     Statistical Downscaling for  prediction of Monthly Mean Land
     Surface Temperatures: Model Documentation", DNMI KLIMA  Report
     02/99 at <URL:
     http://met.no/english/r_and_d_activities/publications/1999.html>.

     For the expression 

                                 Ax=b

     , then the projection of b onto the columns space of A through

                   p= A * inv[t(A) * A] * t(B) * b

     .

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

     MVR(x,y,plot=TRUE,main="Multivariate regression",sub="",test=FALSE,i.eofs=1:8,LINPACK=TRUE, SVD=TRUE)

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

       x: A field or an eof object.

       y: A field or an eof object.

    plot: Flag: plot the diagnostics.

    test: Flag: test by reconstructing one series (leading EOF or a
          grid-box series).

  i.eofs: Which EOFs to include (only when the input is given as eof
          objects).

 LINPACK: 'TRUE': svd; 'FALSE':La.svd

    main: main title (see 'link{plot}').

     sub: subtitle (see 'link{plot}').

     SVD: Flag: determine which approach to use: SVD or
          eigenfunction-based alogithm.

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

     A MVR object that is similar to a field or EOF object (inherits
     the object type, with an additional "MVR" label) with the
     projection (dat), but with additional fields such as the weights
     (psi, which is a map object) [dat represents p and psi represents
     x.hat in Strang (1988)].

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

     R.E. Benestad

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

     ## Not run: 
     data(DNMI.t2m)
     data(DNMI.slp)
     eof.1 <- EOF(DNMI.t2m,mon=1)
     eof.2 <- EOF(DNMI.slp,mon=1)
     mvr <- MVR(eof.1,eof.2)
     ## End(Not run)

