makespline: Monotonic Spline

In aiminy/goseq_test: Gene Ontology analyser for RNA-seq and other length biased data

Description

Fits a monotonic cubic spline to the data provided, using the penalized constrained least squares method from the mgcv package.

Usage

makespline(x, y, newX=NULL, nKnots = 6, lower_bound = 10^-3)

Arguments

x	The predictor variable.
y	The response variable. Must be the same length as x.
newX	The points at which to return the value on the fitted spline. If not specified x is used.
nKnots	The number of knots to use in fitting the spline.
lower_bound	The spline cannot drop below this value.

Details

This uses the pcls function from the mgcv package to produce the fit. The montonicity constraint is enforced using mono.con from the same package. The lower_bound argument is only used on the rare occasions when the fitting function becomes negative or arbitrarily close to zero. If this does occur lower_bound is added everywhere to ensure that no one length is given essentially infinite weighting.

Value

Returns a vector of values containing the value of the fit at each point newX.

Author(s)

Matthew D. Young [e-mail].

References

Package mgcv. In particular this function is a modification of an example given in the man page for pcls.

Examples

y <- c( rbinom(50,p=0.4,size=1), rbinom(50,p=0.6,size=1) )
x <- 1:100
plot(x,y)
p <- makespline(x,y)
lines(x,p)

aiminy/goseq_test documentation built on May 10, 2019, 8 a.m.