geospt (version 1.0-0)

rbf: gaussian, exponential, trigonometric, thin plate spline, inverse multiquadratic, and multiquadratic radial basis function prediction

Description

Function for gaussian (GAU), exponential (EXPON), trigonometric (TRI), thin plate spline (TPS), completely regularized spline (CRS), spline with tension (ST), inverse multiquadratic (IM), and multiquadratic (M) radial basis function (rbf), where rbf is in a local neighbourhood

Usage

rbf(formula, data, eta, rho, newdata, n.neigh, func)

Value

Attributes columns contain coordinates, predictions, and the variance column contains NA's

Details

rbf function generates individual predictions from gaussian (GAU), exponential (EXPON), trigonometric (TRI) thin plate spline (TPS), completely regularized spline (CRS), spline with tension (ST), inverse multiquadratic (IM), and multiquadratic (M) functions

Examples

data(preci)
coordinates(preci) <- ~x+y

# prediction case: one point
point <- data.frame(3,4)
names(point) <- c("x","y")
coordinates(point) <- ~x+y
rbf(prec~x+y, preci, eta=0.1460814, rho=0, newdata=point,n.neigh=10, func="TPS")

# prediction case: a grid of points
puntos<-expand.grid(x=seq(min(preci$x),max(preci$x),0.05), y=seq(min(preci$y),
max(preci$y),0.05))
coordinates(puntos) <- ~x+y
pred.rbf <- rbf(prec~x+y, preci, eta=0.1460814, rho=0, newdata=puntos, n.neigh=10, func="TPS")
coordinates(pred.rbf) = c("x", "y")
gridded(pred.rbf) <- TRUE

# show prediction map
spplot(pred.rbf["var1.pred"], cuts=40, col.regions=bpy.colors(100),
main = "rainfall map TPS", key.space=list(space="right", cex=0.8))