Robust locally weighted regression (Cleveland 1979) with the conventions
of the classic implementation, so that the fit equals that of
stats::lowess(); the fitted values come back in the order of the
input, not sorted.
Usage
lwss(x, y, f = 2/3, iter = 3, delta = NULL)
Arguments
- x, y
The points: finite numbers of equal length.
- f
The share of points in each neighbourhood: positive.
- iter
The number of robustness steps: a whole number from 0.
- delta
Points within delta of the last fitted one are
interpolated: NULL for 1 per cent of the range of x, or a number
from 0.
Value
A numeric vector of fitted values, one per point in input order.
References
Cleveland, W. S. (1979). Robust locally weighted regression
and smoothing scatterplots. Journal of the American Statistical
Association, 74(368), 829-836. doi:10.1080/01621459.1979.10481038
Examples
lwss(c(3, 1, 2, 5, 4), c(2, 1, 3, 6, 4))
#> [1] 2 1 3 6 4
