# 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.

• 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]

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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