## General Instructions

To do each example, just click the Submit

button.
You do not have to type in any R instructions or specify a dataset.
That's already done for you.

## Notes

The handout for smoothing is available in Adobe PDF format. Paper copies were handed out in class. No need to print out another if you got one in class.

## Running Mean Smoother

We use for example data the cholostyramine data from Section 7.3 in Efron and Tibshirani.

### Comments

The R function `ksmooth`

(on-line
help) does simple smoothing.
With `kernel = "box"`

, which is the default, it does a
running mean smoother.

Note that this smooth

is not actually very smooth. This is a property
of the kernel

not being smooth.
In the next section we do better.

Try with different `bandwidth`

values.

## General Kernel Smoother

We use for example data the cholostyramine data from Section 7.3 in Efron and Tibshirani.

### Comments

Again we use the R function `ksmooth`

(on-line
help), this time
with `kernel = "normal"`

.

Try with different `bandwidth`

values.

## Local Polynomial Smoother

We use for example data the cholostyramine data from Section 7.3 in Efron and Tibshirani.

### Comments

The R function `locpoly`

(on-line
help) does local polynomial smoothing.

Try with different `bandwidth`

values.

The function `locpoly`

is in the R package `KernSmooth`

so you must do `library(KernSmooth)`

before using it.

## Smoothing Spline

We use for example data the cholostyramine data from Section 7.3 in Efron and Tibshirani.

### Comments

The R function `smooth.spline`

(on-line
help) does spline smoothing.

Try with different `df`

values.

One can specify the smoothing parameter by using
the `spar`

argument instead of the `df`

argument. The former is the amount of penalty, the latter analogous to
degrees of freedom (effective number of parameters) in the regression function.

One can omit any specification of the smoothing parameter. Then a supposedly optimal choice is made. See the web page about bandwidth selection for more on this.