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)
# }
Community examples
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