constrSpline: Constrained L2 spline.

In helenecharlotte/rSplines: Robust splines

Description

Function to compute a constrained L2 spline.

Usage

constrSpline(t, y, gfun, mp = 100, constr = -1, sign = 1,
  lambda = 1e-04)

Arguments

t	Numeric vector of measurement times.
y	Numeric vector of values to be fitted.
gfun	Choice of Greens function (choose from G1-G10).
mp	Numeric value. Number of points to evaluate spline in.
constr	Numeric value in (-1, 0, 1, 2). Choice of constraint. -1: No constraint. 0: Positivity contraint. 1: Monotonicity constraint. 2: Convexity/concavity constraint.
sign	Numeric value in (-1, 1). 1: Increasing, convexity. -1: Decreasing, concavity.
lambda	Smoothness parameter.

Examples

t = generate.t(m = 25); y = generate.y(type = 2)(t) + generate.noise(t) + generate.noise(t)
plot(t, y, col = "blue")
S = constrSpline(t, y, G3, constr=1)
lines(attr(S, "t"), S)
t = generate.t(m = 25); y = -generate.y(type = 3)(t) + generate.noise(t) + generate.noise(t)
plot(t, y, col = "blue")
S = constrSpline(t, y, G3, constr=2, sign=-1)
lines(attr(S, "t"), S)
t = generate.t(m = 40); y = generate.y(type = 4)(t) + generate.noise(t)
plot(t, y, col = "blue")
S = constrSpline(t, y, G1, constr=0)
lines(t, S)

helenecharlotte/rSplines documentation built on May 17, 2019, 3:24 p.m.