similar to: Stacked Area chart

Is there a package, or does anyone have code they are willing to share, that would allow me to simulate sampling of dead wood pieces across an area? I am specifically looking for code to simulate the dead wood distribution as small line segments across an extent, and then I will "sample" the dead wood using different sampling techniques including line transects, fixed area plots, etc.

Just a quick question. Is there a way to easily specify factor levels in a function definition within nls? For example, I am trying to fit a 3 parameter, nonlinear Weibull function to tree height and I would like to have results by species (or down the road a bit, by plot). I am hoping there is someway to do it easily, similar to the "gas example" in the ANCOVA chapter in Modern

Does someone out there have an example of R-code for a split-split plot ANOVA using aov or another function? The design is not balanced. I never set up one in R before and it would be nice to see an example before I tackle a very complex design I have to model. Thanks, Mike Mike Saunders Research Assistant Forest Ecosystem Research Program Department of Forest Ecosystem Sciences University of

This is a strange request, but I want to build a scatterplot using different image files (jpegs, gif, etc.) as the plot symbols. I have thought about setting this up using a very large layout matrix, but I thought someone might have a better approach. Furthermore, is there any way to have R paste an image file into a specific coordinate within a scatterplot? Thanks in advance, Mike Mike

Could someone give me a hand with the format of the gsummary function? Basically, I have a large set of xyz coordinates generated by LiDAR data (>37 million points) and I am trying to derive various summary statistics on the z-coordinates by a grid cell. I wrote a function to do this by creating factors from the x- and y- coordinates and then using gsummary. However, I want the function to

R community: I have been creating code for plotting nomographs, or multiple, overlain contour plots of z-variables on a common x- and y- variable. My input has been a matrix with observed x, y, and multiple z variables; I then create a trend surface using trmat for each z-variable. So far so good. One application I have for these, requires shading a portion of the nomogram that meets criteria

Dear all, I would like to create a stacked area chart to show the development of species biomass over time. Since it is intended for publication I need to prepare in black and white. I have tried to modify the "stackedPlot" function submitted to this list by Christian Lasarczyk on Tue, 16 Aug 2005 using shading lines rather than colors to distinguish between the species.

r-help at stat.math.ethz.ch on Wednesday, October 26, 2005 at 6:00 AM -0500 wrote: Ronaldo, Try Harold's suggestion. The df still won't agree, because lmer (at least in its current version) just puts an upper bound on the df. But that should be OK, because all those t tests are approximations anyways, and you can get better confidence intervals (credible intervals, whatever) by using the

I am modeling a trend surface using trmat and want to trim the resulting matrix to the area enclosed by my real data (i.e., remove all the extrapolated areas). I was using chull and in.chull to calculate the convex hull and change all the other values created by trmat to NA. However, my real data has portions that are slightly concave so chull would give me slivers that are extrapolations from

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helpeRs, I have a nice looking mosaic plot in an article to be published soon. Sadly, the published version will be in black and white and so ruin the advantage of the default shading scheme of tiles. What would readers suggest as an alternative shading scheme? If I have a black-and-white shading scheme graduated according to suitable cutoffs I won't be able to tell positive from

I was wandering if anybody ever tried to compare the classification accuracy of nnet to other (rpart, tree, bagging) models. From what I know, there is no reason to expect a significant difference in classification accuracy between these models, yet in my particular case I get about 10% error rate for tree, rpart and bagging model and 80% error rate for nnet, applied to the same data. Thanks.

Hi, I am rather new to R, but both myself and another much more experience user cannot figure this out. I have a collegue who has a 800+ nonlinear regressions to run for seed germination (different species, treatments, etc.) over time. I created a looping structure to extract the parameters from each regression; I will then use the parameters themselves for further analysis. I would like to

Hi, I'd like to set up a HA Samba server that serves out data from NFS mounts​. I was thinking that CTDB was the thing to do use but it is only mentioned with serving clustered file systems like Gluster, Lustre, etc. Is there a way to set up a HA Samba server without a clustered file system? ​Thanks, Steve​

Dear R users, I have been having problems getting believable estimates from anova on a model fit from lmer. I get the impression that F is being greatly underestimated, as can be seen by running the example I have given below. First an explanation of what I'm trying to do. I am trying to fit a glmm with binomial errors to some data. The experiment involves 10 shadehouses, divided between

I know this is a long shot, but does anyone out there have code for converting a R-dataframe into a Stand Visualization System (SVS) tree list? It would save me a bit of time. I would be interested if anyone has FVS code as well. I will be working (reworking) NE-TWIGS equations to a regionwide dataset. Thanks in advance, Mike Mike R. Saunders Forest Biometrician Cooperative Forest Research

>>>>> Kurt Hornik writes: I just committed c8761[2-4] to the trunk which adds an internal utility for finding package code using the pipe or function shorthand, teaches R CMD build to add a dependency on R >= 4.1.0 as necessary, and teaches R CMD check to NOTE a missing dependency on R >= 4.1.0, based on Ivan's code. Currently, we seem to have about 1149 packages on

I ran into a problem with "subset" while working at home that I am not sure is a bug or not. I defined a custom function to take a data frame of tree positions, sizes, and types (containing the columns TRT, COMP, PLOT, X, Y, DBH and CON) and wanted to make a stem map of the plot using different symbols and colors to represent the different types of tree stems. I copied a bit of the

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Dear R-ers! Asking for your help with building the stacked area chart for the following simple data (several variables - with date on the X axis): ### Creating a data set my.data<-data.frame(date=c(20080301,20080402,20080503,20090301,20090402,20090503,20100301,20100402,20100503), x=c(1.1,1.0,1.6,1,2,1.5,2.1,1.3,1.9),y=c(-4,-3,-6,-5,-7,-5.2,-6,-4,-4.9),