smoothEnds {stats} R Documentation

## End Points Smoothing (for Running Medians)

### Description

Smooth end points of a vector `y` using subsequently smaller medians and Tukey's end point rule at the very end. (of odd span),

### Usage

```smoothEnds(y, k = 3)
```

### Arguments

 `y` dependent variable to be smoothed (vector). `k` width of largest median window; must be odd.

### Details

`smoothEnds` is used to only do the “end point smoothing”, i.e., change at most the observations closer to the beginning/end than half the window `k`. The first and last value are computed using “Tukey's end point rule”, i.e., `sm[1] = median(y[1], sm[2], 3*sm[2] - 2*sm[3])`.

### Value

vector of smoothed values, the same length as `y`.

Martin Maechler

### References

John W. Tukey (1977) Exploratory Data Analysis, Addison.

Velleman, P.F., and Hoaglin, D.C. (1981) ABC of EDA (Applications, Basics, and Computing of Exploratory Data Analysis); Duxbury.

`runmed(*, end.rule = "median")` which calls `smoothEnds()`.

### Examples

```y <- ys <- (-20:20)^2
y [c(1,10,21,41)] <-  c(100, 30, 400, 470)
s7k <- runmed(y,7, end = "keep")
s7. <- runmed(y,7, end = "const")
s7m <- runmed(y,7)
col3 <- c("midnightblue","blue","steelblue")
plot(y, main = "Running Medians -- runmed(*, k=7, end.rule = X)")
lines(ys, col = "light gray")
matlines(cbind(s7k,s7.,s7m), lwd= 1.5, lty = 1, col = col3)
legend(1,470, paste("end.rule",c("keep","constant","median"),sep=" = "),
col = col3, lwd = 1.5, lty = 1)

stopifnot(identical(s7m, smoothEnds(s7k, 7)))
```

[Package stats version 2.2.1 Index]