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ShapeSelectForest (version 1.1)

ShapeSelectForest-package: Shape Selection for Landsat Time Series of Forest Dynamics

Description

Given a scatterplot of $(x_i, y_i)$, $i = 1,\ldots,n$, where $\bold{x}$ could be a vector of years and $\bold{y}$ could be a vector of Landsat signals, constrained least-squares spline fits are obtained for the following shapes:
  • 1. flat
2. decreasing 3. one-jump, i.e., decreasing, jump up, decreasing 4. inverted vee (increasing then decreasing) 5. vee (decreasing then increasing) 6. linear increasing 7. double-jump, i.e., decreasing, jump up, decreasing, jump up, decreasing.

Arguments

code

shape

Details

ll{ Package: ShapeSelectForest Type: Package Version: 1.1 Date: 2015-09-06 License: GPL (>= 2) }

References

Meyer, M. C. and Woodroofe M (2000) On the Degrees of Freedom in Shape-Restricted Regression. The Annals of Statistics 28, 1083--1104.

Meyer, M. C. (2013a) Semi-parametric additive constrained regression. Journal of Nonparametric Statistics 25(3), 715.

Meyer, M. C. (2013b) A simple new algorithm for quadratic programming with applications in statistics. Communications in Statistics 42(5), 1126--1139.

Liao, X. and M. C. Meyer (2014) coneproj: An R package for the primal or dual cone projections with routines for constrained regression. Journal of Statistical Software 61(12), 1--22.