loess.ci: Loess with confidence intervals

In spatialEco: Spatial Analysis and Modelling Utilities

Loess with confidence intervals

Description

Calculates a local polynomial regression fit with associated confidence intervals

Usage

loess.ci(y, x, p = 0.95, plot = FALSE, ...)

Arguments

y	Dependent variable, vector
x	Independent variable, vector
p	Percent confidence intervals (default is 0.95)
plot	Plot the fit and confidence intervals
...	Arguments passed to loess

Value

A list object with:

• loess Predicted values

• se Estimated standard error for each predicted value

• lci Lower confidence interval

• uci Upper confidence interval

• df Estimated degrees of freedom

• rs Residual scale of residuals used in computing the standard errors

Author(s)

Jeffrey S. Evans [e-mail]

References

W. S. Cleveland, E. Grosse and W. M. Shyu (1992) Local regression models. Chapter 8 of Statistical Models in S eds J.M. Chambers and T.J. Hastie, Wadsworth & Brooks/Cole.

Examples

 x <- seq(-20, 20, 0.1)
 y <- sin(x)/x + rnorm(length(x), sd=0.03)
 p <- which(y == "NaN")
   y <- y[-p]	
   x <- x[-p]
 
opar <- par(no.readonly=TRUE)
  par(mfrow=c(2,2))  
    lci <- loess.ci(y, x, plot=TRUE, span=0.10)
    lci <- loess.ci(y, x, plot=TRUE, span=0.30)
    lci <- loess.ci(y, x, plot=TRUE, span=0.50)
    lci <- loess.ci(y, x, plot=TRUE, span=0.80)
par(opar)

spatialEco documentation built on Nov. 18, 2023, 1:13 a.m.