spatialEco (version 1.3-2)

loess.ci: 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

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)

# }