plot.SiZer {SiZer} | R Documentation |
Plot a SiZer
object that was created using SiZer()
.
## S3 method for class 'SiZer'. ## S3 method for class 'SiZer': plot(x, ylab = expression(log[10](h)), colorlist = c("red", "purple", "blue", "grey"), ...)
x |
An object created using SiZer() |
ylab |
What the y-axis should be labled. |
colorlist |
What colors should be used. This is a vector that corresponds to 'decreasing', 'possibley zero', 'increasing', 'insufficient data' |
... |
Any other parameters to be passed to the function image . |
The white lines in the SiZer map give a graphical representation of the bandwidth. The horizontal distance between the lines is 2h.
None
Derek Sonderegger
Chaudhuri, P., and J. S. Marron. 1999. SiZer for exploration of structures in curves. Journal of the American Statistical Association 94:807-823.
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.
plot.SiZer
, locally.weighted.polynomial
data('Arkansas') x <- Arkansas$year y <- Arkansas$sqrt.mayflies # Calculate the SiZer map for the first derivative SiZer.1 <- SiZer(x, y, h=c(.5,10), degree=1, derv=1) plot(SiZer.1) # Calculate the SiZer map for the second derivative SiZer.2 <- SiZer(x, y, h=c(.5,10), degree=2, derv=2); plot(SiZer.2) # By setting the grid.length larger, we get a more detailed SiZer # map but it takes longer to compute. SiZer.3 <- SiZer(x, y, h=c(.5,10), grid.length=100, degree=1, derv=1) plot(SiZer.3)