plot.LocallyWeightedPolynomial {SiZer} | R Documentation |
Creates a plot of an object created by locally.weighted.polynomial
.
## S3 method for class 'LocallyWeightedPolynomial': plot(x, derv = 0, CI.method = 2, alpha = 0.05, use.ess = TRUE, draw.points = TRUE, ...)
x |
LocallyWeightedPolynomial object |
derv |
Derivative to be plotted. Default is 0 - which plots the smoothed function. |
CI.method |
What method should be used to calculate the confidence interval about the estimated line. The methods are from Hannig and Marron (2006), where 1 is the point-wise estimate, and 2 is the row-wise estimate. |
alpha |
The CI has a 1-alpha/2 level of significance. |
use.ess |
ESS stands for the estimated sample size. If at any point along the x-axis, the ESS is too small, then we will not plot unless use.ess=FALSE. |
draw.points |
Should the data points be included in the graph? |
... |
Additional arguments to be passed to the graphing functions. |
Derek Sonderegger
Hannig, J., and J. S. Marron. 2006. Advanced distribution theory for SiZer. Journal of the American Statistical Association 101:484-499.
Sonderegger, D., Wang, H., Clements, W. H., and Noon, B. R. 2008. Using SiZer to detect thresholds in ecological data. Frontiers in Ecology and the Environment To Appear.
data('Arkansas') x <- Arkansas$year y <- Arkansas$sqrt.mayflies model <- locally.weighted.polynomial(x,y) plot(model) model <- locally.weighted.polynomial(x,y,degree=2) plot(model, derv=1) plot(model, derv=2)