Description Usage Arguments Details Value See Also Examples
Generates a table with the results of the evaluation of radial basis functions (rbf): gaussian (GAU), exponential (EXPON), trigonometric (TRI), thin plate spline (TPS), completely regularized spline (CRS), spline with tension (ST), inverse multiquadratic (IM), and multiquadratic (M) from the leave-one-out cross validation method.
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formula |
formula that defines the dependent variable as a linear model of independent variables; suppose the dependent variable has name z, for a rbf detrended use z~1, for a rbf with trend, suppose z is linearly dependent on x and y, use the formula z~x+y (linear trend). |
data |
SpatialPointsDataFrame: should contain the dependent variable, independent variables, and coordinates. |
eta |
the optimal smoothing parameter; we recommend using the parameter found by minimizing the root-mean-square prediction errors using cross-validation |
rho |
value of optimal parameter robustness; we recommend using the parameter
found by minimizing the root-mean-square prediction errors using cross-validation.
eta and rho parameters can be optimized simultaneously, through the |
n.neigh |
number of nearest observations that should be used for a rbf prediction, where nearest is defined in terms of the spatial locations |
func |
radial basis function model type, e.g. "GAU", "EXPON", "TRI", "TPS", "CRS", "ST", "MI" and "M", are currently available |
Leave-one-out cross validation (LOOCV) visits a data point, predicts the value at that location by leaving out the observed value, and proceeds with the next data point. The observed value is left out because rbf would otherwise predict the value itself.
data frame contain the data coordinates, prediction columns, observed values, residuals, the prediction variance, zscore (residual divided by standard error) which left with NA's, and the fold column which is associated to cross-validation count. Prediction columns and residuals are obtained from cross-validation data points
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Loading required package: gstat
Loading required package: genalg
Loading required package: MASS
Loading required package: sp
Loading required package: minqa
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var1.pred var1.var observed residual zscore fold x y
1 398.3808 NA 420 21.6191767 NA 1 1 4
2 412.5996 NA 410 -2.5996082 NA 2 1 2
3 420.0921 NA 405 -15.0921052 NA 3 3 3
4 419.1315 NA 415 -4.1315291 NA 4 3 0
5 429.4019 NA 430 0.5981334 NA 5 5 1
6 418.6864 NA 425 6.3136167 NA 6 5 3
7 422.8531 NA 415 -7.8530624 NA 7 6 4
8 433.6800 NA 435 1.3200272 NA 8 6 1
9 424.7823 NA 425 0.2177269 NA 9 6 3
10 431.4525 NA 430 -1.4524893 NA 10 7 2
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