# loess.boot: Loess Bootstrap In jeffreyevans/spatialEco: Spatial Analysis and Modelling Utilities

## Description

Bootstrap of a Local Polynomial Regression (loess)

## Usage

 `1` ```loess.boot(x, y, nreps = 100, confidence = 0.95, ...) ```

## Arguments

 `x` Independent variable `y` Dependent variable `nreps` Number of bootstrap replicates `confidence` Fraction of replicates contained in confidence region `...` Additional arguments passed to loess function

## Value

nreps Number of bootstrap replicates

confidence Confidence interval (region)

span alpha (span) parameter used loess fit

degree polynomial degree used in loess fit

normalize Normalized data (TRUE/FALSE)

family Family of statistic used in fit

parametric Parametric approximation (TRUE/FALSE)

surface Surface fit, see loess.control

data data.frame of x,y used in model

fit data.frame including: x Equally-spaced x index (see NOTES) y.fit loess fit up.lim Upper confidence interval low.lim Lower confidence interval stddev Standard deviation of loess fit at each x value

## Note

The function fits a loess curve and then calculates a symmetric nonparametric bootstrap with a confidence region. Fitted curves are evaluated at a fixed number of equally-spaced x values, regardless of the number of x values in the data. Some replicates do not include the values at the lower and upper end of the range of x values. If the number of such replicates is too large, it becomes impossible to construct a confidence region that includes a fraction "confidence" of the bootstrap replicates. In such cases, the left and/or right portion of the confidence region is truncated.

## Author(s)

Jeffrey S. Evans <[email protected]>

## References

Cleveland, WS, (1979) Robust Locally Weighted Regression and Smoothing Plots Journal of the American Statistical Association 74:829-836

Efron, B., and R. Tibshirani (1993) An Introduction to the Bootstrap Chapman and Hall, New York

Hardle, W., (1989) Applied Nonparametric Regression Cambridge University Press, NY.

Tibshirani, R. (1988) Variance stabilization and the bootstrap. Biometrika 75(3):433-44.

## Examples

 ```1 2 3 4 5``` ``` n=1000 x <- seq(0, 4, length.out=n) y <- sin(2*x)+ 0.5*x + rnorm(n, sd=0.5) sb <- loess.boot(x, y, nreps=99, confidence=0.90, span=0.40) plot(sb) ```

jeffreyevans/spatialEco documentation built on Jan. 15, 2019, 11:15 a.m.