supsmu {stats} | R Documentation |

## Friedman's SuperSmoother

### Description

Smooth the (x, y) values by Friedman's “super smoother”.

### Usage

supsmu(x, y, wt, span = "cv", periodic = FALSE, bass = 0)

### Arguments

`x` |
x values for smoothing |

`y` |
y values for smoothing |

`wt` |
case weights, by default all equal |

`span` |
the fraction of the observations in the span of the running
lines smoother, or `"cv"` to choose this by leave-one-out
cross-validation. |

`periodic` |
if `TRUE` , the x values are assumed to be in
`[0, 1]` and of period 1. |

`bass` |
controls the smoothness of the fitted curve. Values of up
to 10 indicate increasing smoothness. |

### Details

`supsmu`

is a running lines smoother which chooses between three
spans for the lines. The running lines smoothers are symmetric, with
`k/2`

data points each side of the predicted point, and values of
`k`

as `0.5 * n`

, `0.2 * n`

and `0.05 * n`

, where
`n`

is the number of data points. If `span`

is specified,
a single smoother with span `span * n`

is used.

The best of the three smoothers is chosen by cross-validation for each
prediction. The best spans are then smoothed by a running lines
smoother and the final prediction chosen by linear interpolation.

The FORTRAN code says: “For small samples (`n < 40`

) or if
there are substantial serial correlations between observations close
in x-value, then a prespecified fixed span smoother (```
span >
0
```

) should be used. Reasonable span values are 0.2 to 0.4.”

### Value

A list with components

`x` |
the input values in increasing order with duplicates removed. |

`y` |
the corresponding y values on the fitted curve. |

### References

Friedman, J. H. (1984)
SMART User's Guide.
Laboratory for Computational Statistics, Stanford University Technical
Report No. 1.

Friedman, J. H. (1984)
A variable span scatterplot smoother.
Laboratory for Computational Statistics, Stanford University Technical
Report No. 5.

### See Also

`ppr`

### Examples

with(cars, {
plot(speed, dist)
lines(supsmu(speed, dist))
lines(supsmu(speed, dist, bass = 7), lty = 2)
})

[Package

*stats* version 2.1.0

Index]