# mspline

From mda v0.4-10
by Trevor Hastie

##### Vector Smoothing Spline

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).

- y
response matrix.

- 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.

##### Details

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

,
and allows for simultaneous smoothing of multiple responses

##### Value

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

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

The df used (in case lambda was supplied)

A matrix like `y`

of smoothed responses

Self influences (diagonal of smoother matrix)

##### See Also

##### Examples

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

*Documentation reproduced from package mda, version 0.4-10, License: GPL-2*

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