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grdtrend(1)                           GMT                          grdtrend(1)


       grdtrend - Fit trend surface to grids and compute residuals


       grdtrend  grdfile   -Nn_model[+r]  [  ]  [   -Rregion  ]  [ ] [ ]

       Note: No space is allowed between the option flag  and  the  associated


       grdtrend reads a 2-D grid file and fits a low-order polynomial trend to
       these data by [optionally weighted] least-squares. The trend surface is
       defined by:
          m1  + m2*x + m3*y + m4*x*y + m5*x*x + m6*y*y + m7*x*x*x + m8*x*x*y +
          m9*x*y*y + m10*y*y*y.

       The user must specify -Nn_model, the number of model parameters to use;
       thus,  -N3  fits  a bilinear trend, -N6 a quadratic surface, and so on.
       Optionally, append +r to the -N option to perform a robust fit. In this
       case,  the program will iteratively reweight the data based on a robust
       scale estimate, in order to converge to a solution insensitive to  out-
       liers.  This  may  be  handy  when separating a aregionala field from a
       aresiduala which should have non-zero mean, such as a local mountain on
       a regional surface.

       If  data  file has values set to NaN, these will be ignored during fit-
       ting; if output files are written, these will also have NaN in the same


              The name of a 2-D binary grid file.

              n_model  sets  the number of model parameters to fit.  Append +r
              for robust fit.

              Write the difference (input data - trend) to the file

       -Rxmin/xmax/ymin/ymax[+r][+uunit] (more a|)
              Specify the region of interest. Using the -R option will  select
              a  subsection  of the input grid. If this subsection exceeds the
              boundaries  of  the  grid,  only  the  common  region  will   be
              Write the fitted trend to the file

       -V[level] (more a|)
              Select verbosity level [c].
              If  exists,  it  will  be  read  and  used to solve a
              weighted least-squares problem. [Default: Ordinary least-squares
              fit.]  If  the robust option has been selected, the weights used
              in the robust fit will be written to

       -^ or just -
              Print a short message about the  syntax  of  the  command,  then
              exits (NOTE: on Windows just use -).

       -+ or just +
              Print  an extensive usage (help) message, including the explana-
              tion of any module-specific  option  (but  not  the  GMT  common
              options), then exits.

       -? or no arguments
              Print a complete usage (help) message, including the explanation
              of all options, then exits.


       The domain of x and y will be shifted and scaled to  [-1,  1]  and  the
       basis  functions  are  built  from  Legendre  polynomials. These have a
       numerical advantage in the form of the matrix which  must  be  inverted
       and  allow  more  accurate solutions. NOTE: The model parameters listed
       with -V are Legendre polynomial coefficients; they are not  numerically
       equivalent  to the m#s in the equation described above. The description
       above is to allow the user to match -N with the order of the polynomial
       surface.  See  grdmath  if  you  need  to  evaluate the trend using the
       reported coefficients.


       By default GMT  writes  out  grid  as  single  precision  floats  in  a
       COARDS-complaint  netCDF  file  format. However, GMT is able to produce
       grid files in many other commonly  used  grid  file  formats  and  also
       facilitates  so  called  apackinga of grids, writing out floating point
       data as 1- or 2-byte integers. (more a|)


       To remove a planar  trend  from  and  write  result  in

              gmt grdtrend -N3

       To  do a robust fit of a bicubic surface to, writing the
       result in and the weights used in, and
       reporting the progress:

              gmt grdtrend -N10+r -V


       gmt(1), grdfft(1), grdfilter(1), grdmath(1)


       2017, P. Wessel, W. H. F. Smith, R. Scharroo, J. Luis, and F. Wobbe

5.4.2                            Jun 24, 2017                      grdtrend(1)

gmt5 5.4.2 - Generated Thu Jun 29 08:31:07 CDT 2017
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