Description Usage Arguments Details Value Examples

View source: R/EFDR_functions.R

Given a data frame with fields `x, y`

and `z`

, `regrid`

returns a data frame with
fields `x, y`

and `z`

, this time with `x, y`

arranged on a regular grid of size `n2`

by
`n1`

.

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`df` |
data frame with fields |

`n1` |
image length in pixels |

`n2` |
image height in pixels |

`method` |
method to be used, see details |

`idp` |
inverse distance power |

`nmax` |
when using inverse distance weighting, the number of nearest neighbours to consider when interpolating using idw. When using conditional simulation, the number of nearest observations to used for a kriging simulation |

`model` |
the model type when using conditional simulation (use |

There are three supported methods for regridding. The first, "idw", is
the inverse-distance-weighting method. The function overlays a grid over the data.
The cells are constructed evenly within the bounding
box of the data and filled with interpolated values using the inverse weighting distance metric
with power `idp`

. `nmax`

determines the maximum number of neighbours when using the distance weighting.
With this method, interpolation uses the inverse distance weight function `gstat`

in the `gstat`

package.
Refer to the package `gstat`

for more details and formulae.

The second method "cond_sim" uses conditional simulation to generate a realisation of
the unobserved process at the grid points. This is a model-based approach, and the
variogram model may be selected through the parameter `model`

. The exponential
variogram is used by default. For a complete list of possible models use `gstat::vgm()`

.
For a tutorial on how the conditional simulation is carried out see the `gstat`

vignette.

The third method "median_polishing" applies a median polish to the data. First, a grid is overlayed. If more than one
data point is present in each grid box, the mean of the data is taken. Where there is no data, the grid box is assigned
a value of NA. This gridded image is then passed to the function `medpolish`

which carried out Tukey's median
polish procedure to obtain an interpolant of the form *z(s) = μ + a(s1) + b(s2)* where *s1* is the x-axis and
*s2* is the y-axis. Missing points in the gridded image are then replaced with *z(s)* evaluated at these points. This method
cannot be used if all rows and columns do not contain at least one data point.

data frame with fields `x,y,z`

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andrewzm/EFDR documentation built on May 10, 2017, 9:27 p.m.

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