lpc.project {LPCM} | R Documentation |
Projection onto LPC
Description
Projects a new observation onto the spline representation of the local principal curve.
Usage
lpc.project(object, newdata, ...)
Arguments
object |
Object of class |
newdata |
A data frame containing the new data to be projected. |
... |
Additional arguments to be passed to |
Value
closest.pi |
Projection index of projected point(s) (in cubic spline parametrization). |
closest.or.pi |
Projection index of projected point(s) (in terms of the original LPC parametrization). |
closest.coords |
Coordinates of projected data point(s) |
closest.dist |
Euclidean distance between data point(s) and their projected counterpart(s). |
closest.branch |
ID of branch onto which the data point was
projected (the IDs get allocated in the output component
|
Note
The parametrization of the cubic spline function is not exactly the same as that of the original LPC. The reason is that the latter uses Euclidean distances between centers of masses, while the former uses the arc length along the cubic spline. The differences are normally quite small, though.
Author(s)
J. Einbeck and L. Evers
References
Einbeck, J., Evers, L. & Hinchliff, K. (2010): Data compression and regression based on local principal curves. In A. Fink, B. Lausen, W. Seidel, and A. Ultsch (Eds), Advances in Data Analysis, Data Handling, and Business Intelligence, Heidelberg, pp. 701–712, Springer.
See Also
Examples
data(gvessel)
gvessel.lpc <- lpc(gvessel[,c(2,4,5)], scaled=TRUE, h=0.11, x0=c(35, 1870, 6.3))
lpc.project(gvessel.lpc, newdata=data.frame(salg=35,dephtg= 2000,oxyg=6))