loess.ci

From spatialEco v1.3-2 by Jeffrey S Evans

Loess with confidence intervals

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

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

# NOT RUN {
 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)

# }

Documentation reproduced from package spatialEco, version 1.3-2, License: GPL-3

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