loess.ci

0th

Percentile

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.

Aliases
  • loess.ci
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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