msSmoothSpline: Fit a Smooth Curve Using Cubic Spline

In zeehio/msProcess: Protein Mass Spectra Processing

Description

Fits a cubic spline curve to a subset or set of data points and returns a vector of fitted smooth curve values evaluated at the original locations.

Usage

msSmoothSpline(x, y, df=30, spar=0, cv=FALSE, all.knots=FALSE,
    df.offset=0, penalty=1, index=rep(TRUE, length(x)),
    process="msSmoothSpline")

Arguments

x	A numeric vector of abscissa values.
y	A numeric vector of ordinate values, which must be of the same length of x.
df, spar, cv, all.knots, df.offset, penalty	See function smooth.spline for descriptions.
index	A logical vector of the same length of x indicating the elements to be used in the fitting. Deafult: rep(TRUE, length(x)).
process	A character string denoting the name of the process to register with the (embedded) event history object of the input after processing the input data. Default: "msSmoothSpline".

Value

A numeric vector of fitted smooth curve values evaluated at the original locations.

See Also

msSmoothApprox, msSmoothKsmooth, msSmoothLoess, msSmoothMean, msSmoothMonotone, msSmoothSupsmu.

zeehio/msProcess documentation built on May 4, 2019, 10:15 p.m.