# mspline: Vector Smoothing Spline

## Description

Fit a smoothing spline to a matrix of responses, single x.

## Usage

mspline(x, y, w, df = 5, lambda, thresh = 1e-04, …)

## Arguments

x

x variable (numeric vector).

w

optional weight vector, defaults to a vector of ones.

df

requested degrees of freedom, as in `smooth.spline`

.

lambda

can provide penalty instead of df.

thresh

convergence threshold for df inversion (to lambda).

…

holdall for other arguments.

## Value

A list is returned, with a number of components, only some of which
are of interest. These are

lambdaThe value of lambda used (in case df was supplied)

dfThe df used (in case lambda was supplied)

sA matrix like `y`

of smoothed responses

levSelf influences (diagonal of smoother matrix)

## Details

This function is based on the ingredients of `smooth.spline`

,
and allows for simultaneous smoothing of multiple responses

## Examples

# NOT RUN {
x=rnorm(100)
y=matrix(rnorm(100*10),100,10)
fit=mspline(x,y,df=5)
# }