| Paketname | liblip2 |
| Beschreibung | reliable interpolation of multivariate scattered data |
| Archiv/Repository | Offizielles Debian Archiv squeeze (main) |
| Version | 2.0.0-1.1 |
| Sektion | libs |
| Priorität | optional |
| Installierte Größe | 476 Byte |
| Hängt ab von | libc6 (>= 2.7-1), libgcc1 (>= 1:4.1.1-21), libstdc++6 (>= 4.1.1-21) |
| Empfohlene Pakete | |
| Paketbetreuer | Juan Esteban Monsalve Tobon |
| Quelle | liblip |
| Paketgröße | 299640 Byte |
| Prüfsumme MD5 | e6696601391dada193852c6d5895a755 |
| Prüfsumme SHA1 | 0cf46b4f101c9e211a26b8da2b0d046e7caf4b78 |
| Prüfsumme SHA256 | 2a1e903cadc55053dd091299aa7d21e9a1d7500d8c9a3e3a72a0769d084a949e |
| Link zum Herunterladen | liblip2_2.0.0-1.1_i386.deb |
| Ausführliche Beschreibung | Lip interpolates scattered multivariate data with a Lipschitz function.
.
Methods of interpolation of multivariate scattered data are scarce.
The programming library Lip implements a
new method by G. Beliakov, which relies on building reliable lower and
upper approximations of Lipschitz functions. If we assume that the
function that we want to interpolate is Lipschitz-continuous, we can
provide tight bounds on its values at any point, in the worse case
scenario. Thus we obtain the interpolant, which approximates the unknown
Lipschitz function f best in the worst case scenario. This translates
into reliable learning of f, something that other methods cannot do (the
error of approximation of most other methods can be infinitely large,
depending on what f generated the data).
.
Lipschitz condition implies that the rate of change of the function is
bounded:
.
|f(x)-f(y)| |