similar to: gsummary

Full_Name: Ben Saville Version: 2.1 OS: Windows XP Submission from: (NULL) (152.2.94.145) I'm using the gsummary function to calculate a sum of V1 (column one) from my data 'mytest' by group (V2,or column 2). If V1 (the variable of interest) is all the same value (in this case all 2's), I do not get back the correct summation. If there is at least one difference in V1 (all

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

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.

Dear R-users, I am a newbie to this site and a relative new-comer to S/R, so please tread lightly, for you tread... There have been several posting relating to problems with augPred() from the nlme library. Here is a "fix" for one of these problems which may lie at the root of others. In my case the problem with augPred() lay in gsummary(), which augPred() uses, causing it to fail.

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

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

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

I wish to do a stacked area chart to show how relative proportions of species within a stand have changed over time. I know this is simple, but can someone point me to the right function (if it exists). I have not had any luck finding it in the R-help, but maybe I am searching using the wrong keywords. Thanks, Mike Mike Saunders Research Assistant Forest Ecosystem Research Program Department

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

I have got following error in drawing wavelet fitting. can some one help? > library(faraway) > data(lidar) > newlidar<-lidar[c(1:128),] > library(wavethresh) > wds <- wd(newlidar$logratio) > draw(wds) Error in plot.default(x = x, y = zwr, main = main, sub = sub, xlab = xlab, : formal argument "type" matched by multiple actual arguments [[alternative HTML

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

Hi All, I am a PhD student in forestry science and I am working with LiDAR data set (huge data set). I am a brand-new in R and geostatistic (SORRY, my background it?s in forestry) but I wish improve my skill for improve myself. I wish to develop a methodology to processing a large data-set of points (typical in LiDAR) but there is a problem with memory. I had created a subsample data-base but

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Hi, I've collected quite a bit of elevation data (LIDAR elevation points) and am looking for a suitable platform to do analysis and modeling on it. The data is sitting in an Oracle database, one table, 200 million rows of x,y, and z. I'm trying to figure out what hardware resources we need to reserve in order to run 64 BIT R for this size data. Here's my question: Is the 64 BIT

Hi I am afraid i am not understanding something very fundamental.... and does not matter how much i am looking into the book "Generalized Additive Models" of S. Wood i still don't understand my result. I am trying to model presence / absence (presence = 1, absence = 0) of a species using some lidar metrics (i have 4 of these). I am using different models and such .... and when i

Dear all, Sometime I need to change data column name,but I catn't do it. example: type<-c("max","min") test<-data.frame(class=c("a","a","a","b","b"),value=1:5) for (i in 2:length(type)) { tmp<-gsummary(test,FUN=type[i],groups=test$class) tmp1<-data.frame(class=tmp$class,

OK, I really dread to ask that .... much more that I know some discussion about p-values and if they are relevant for regressions were already on the list. I know to get p-val of regression coefficients - this is not a problem. But unfortunately one editor of a journal where i would like to publish some results insists in giving p-values for the squared deviance i get out from different glm and

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Dear R-Help members, I am using Simon Wood`s mgcv package version1.7-22and R version 3.0.0 (2013-04-03) for fitting a GAM-Model to the LIDAR Data contained in the "SemiPar" package. Here is the code for fitting the model and for plotting the result: data("lidar") attach(lidar) ### # mgcv fitting ### gam_fit <- gam(logratio ~ s(range, k = 40, bs = "cr"), gamma

I've got a data frame that looks like this: subject foo bar 2 1.7 3.2 2 2.3 4.1 3 7.6 2.3 3 7.1 3.3 3 7.3 2.3 3 7.4 1.3 5 6.2 6.1 5 3.4 6.9 ... That is, I've got multiple rows per subject. I need to compute summaries within categories where the subject has the same number