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 initialized simulation.

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

     `SimulateRF' internal function; use `GaussRF' and `MaxStableRF',
     instead.

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

     DoSimulateRF(n=1, register=0)

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

     SimulateRF(x, y=NULL, z=NULL, grid, model, param, method=NULL,
               n=1, 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

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

  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 occured during the
     initialisation process, and a positive value if failed.

     `SimulateRF' and `DoSimulateRF' return `NULL' if an error has
     occured; 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@uni-bayreuth.de <URL:
     http://www.geo.uni-bayreuth.de/~martin>

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

     `GaussRF', `MaxStableRF', `RandomFields'

