ssr3d_predict {sisireg} | R Documentation |
3-dimensional SSR model prediction
Description
Calculates the prediction for a given 3-dimensional SSR model.
Usage
ssr3d_predict(df_model, xy, ms = FALSE)
Arguments
df_model |
data frame with model coordinates. |
xy |
data frame with coordinates for prediction. |
ms |
optional: boolean value to use the minimal surface algorithm. |
Value
z |
array with predictions. |
Author(s)
Dr. Lars Metzner
References
Dr. Lars Metzner (2021) Adäquates Maschinelles Lernen. Independently Published.
Examples
# generate data
set.seed(1234)
x <- rnorm(900)
y <- rnorm(900)
xy <- data.frame(x=x, y=y)
z <- rnorm(900) + atan2(x, y)
# Training
df_model <- ssr3d(xy, z)
# Prediction
xx <- c(c(0,1), c(-1,1), c(1,-1))
xx <- matrix(xx, ncol = 2)
yy <- ssr3d_predict(df_model, xx)
[Package sisireg version 1.1.1 Index]