Hello list members, I am working with simulated data for landscape pattern analysis. I have 1000 replicates of binary (2 colour) gridded landscapes at each combination of 9 levels of class proportion and 11 levels of spatial autocorrelation. The results are stored in an array as follows:
> dim(surfaces) [1] 38 9 11 1000 The dimensions are defined as follows: [x,,,] 1:38, integers that identify a measurement type (landscape pattern metrics) [,x,,] 1:9, integers that identify levels of class proportion [,,x,] 1:11, integers that identify levels of spatial autocorrelation [,,,x] floating point values for the specific landscape metric I would like a simple way to produce boxplots of the 1000 metric values for a specific landscape metric and level of spatial autocorrelation across the 9 levels of proportion. Thus, I want to fix the first dimension (say as 10) and fix the third dimension (say as 1), and then use the second dimension as factors (1:9) to produce boxplots of the values in the 4th dimension. Is there a simple way to do this? I have been playing with boxplot() and apply() but am getting some dimensions mixed up and thought that this would be a good time to seek some help. Any help with this would be greatly appreciated. Thank you, Tarmo _____________________________________ Tarmo K Remmel PhD Associate Professor, Department of Geography York University, N413A Ross Building 4700 Keele Street, Toronto, Ontario, M3J 1P3 Tel: 416-736-2100 x22496, Fax: 416-736-5988 Skype: tarmoremmel ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
