SimulateRF           package:RandomFields           R Documentation

_S_i_m_u_l_a_t_i_o_n _o_f _R_a_n_d_o_m _F_i_e_l_d_s

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

     'DoSimulateRF' performs an already initialised simulation.

     'InitSimulateRF' internal function; use 'InitGaussRF' and
     'InitMaxStableRF', instead.

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

     DoSimulateRF(n=1, register=0)

     InitSimulateRF(x, y=NULL, z=NULL, T=NULL, grid, model, param, trend,
                    method=NULL, register=0, gridtriple=FALSE, distribution=NA)

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

       x: matrix of coordinates, or vector of x coordinates

       y: vector of y coordinates

       z: vector of z coordinates

       T: time instances

    grid: logical; determines whether the vectors 'x', 'y', and 'z'
          should be interpreted as a grid definition, see Details.

   model: string; covariance or variogram model, see 'CovarianceFct',
          or type 'PrintModelList()' to get all options

   param: vector or list.  'param=c(mean, variance, nugget, scale,
          ...)',  'param=list(c(variance, scale, ...), ...,
          c(variance,scale,...))', 'param=matrix(...)', or
          'param=list(list(variance, anisotropy, kappa),...,
          list(variance, anisotropy, kappa))'; the parameters must be
          given in this order; further parameters are to be added in
          case of a parametrised class of models, see 'CovarianceFct'

   trend: Not programmed yet. trend surface: number (mean),  vector of
          length d+1 (linear trend a_0 +a_1 x_1 + ... + a_d x_d), or
          function

  method: 'NULL' or string; Method used for simulating, see
          'RFMethods', or type 'PrintMethodList()' to get all options

       n: number of realisations to generate

register: 0:9; place where intermediate calculations are stored; the
          numbers are aliases for 10 internal registers

gridtriple: logical;  if 'gridtriple==FALSE' ascending sequences for
          the parameters  'x', 'y', and 'z' are expected; if
          'gridtriple==TRUE' triples of form 'c(start,end,step)' 
          expected; this parameter is used only if 'grid==TRUE'

distribution: marginal distribution:
           'Gauss', 'Poisson', or 'MaxStable'.

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

     'InitSimulateRF' returns 0 if no error has occurred during the
     initialisation process, and a positive value if failed.

     'DoSimulateRF' returns 'NULL' if an error has occurred; otherwise
     the returned object depends on the parameters 'n' and 'grid':
      'n==1':
      * 'grid==FALSE'.  A vector of simulated values is returned
     (independent of the dimension of the random field)
      * 'grid==TRUE'.  An array of the dimension of the random field is
     returned.

     'n>1':
      * 'grid==FALSE'.  A matrix is returned.  The columns contain the
     repetitions.
      * 'grid==TRUE'.  An array of dimension d+1, where d is the
     dimension of the random field, is returned.  The last dimension
     contains the repetitions.

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

     Martin Schlather, martin.schlather@cu.lu <URL:
     http://www.cu.lu/~schlathe>

_S_e_e _A_l_s_o:

     'GaussRF', 'MaxStableRF', 'RandomFields'

