similar to: function output with for loop and if statement

Hi, I would like to construct a transition matrix from a data frame with annual transitions of marked plants. plant<-c(1:6) class<-c("seed","seed", "seed", "veg", "rep", "rep") fate<-c("dead", "veg","veg","rep", "rep", "veg") trans<-data.frame(plant, class, fate)

i want to tag categories to its menuname. i have a csv containing menu item name and in other csv i have a column containing some strings, i want to pick that strings from categories and look into menu items if any menu item containing that string i want to create a new column next to menu item name flagged as 1 otherwise 0 and the only condition is once a menu item flagged as 1 i don't need

Hello. First post, though I have read scores. Mostly i can solve my problems reading the archives, but I lack the vocabulary to ask this one right. Any social faux pais, I apologize. I am sure this is a very basic question and I am embarrassed to ask, but I spent several hours scouring the archives and trying various suggestions, but I am too new to get any of them to work. I am trying to

Hi R listers, I am trying to group distances of nests to the vegetation into classes that are define by (0-5m, 6-10m, 11-15m, 16-20m, 21-25m, 26-30m, 31-35m, 36-40m, 41-45m, 46-50m, 51-55m, 56-60m). Each row is a nest and all the distances to the vegetation is in a column. In plyr, I have tried - below script but I think I am going about this the wrong way and am not successful. #Veg index

Hi all, How can I overlay these two histograms? ggplot(gg, aes(gg$Alz, fill = gg$veg)) + geom_histogram(alpha = 0.2) ggplot(tt, aes(tt$Cont, fill = tt$veg)) + geom_histogram(alpha = 0.2) thanks for any help! Elahe

Hello all, I am going slightly mad trying to create a table for running co-correspondence analysis. What I have is seed bank and vegetation data, and my aim is to see if the vegetation found in a site (containing several seed bank samples) can predict the composition of a seed bank sample within that site. So for this I need two tables with matching rows. I have created an empty matrix,

Hi All, I am wondering if anyone can tell me what the warning message below the model means? J add1(DTA.glm,~ Aeventexhumed + Veg + Berm + HTL + Estuary + Rayos) Single term additions Model: cbind(MaxHatch, TotalEggs - MaxHatch) ~ Aeventexhumed + Veg + Berm + HTL Df Deviance AIC <none> 488.86 4232.9 Estuary 1 454.96 4201.0 Rayos 3 258.80 4008.9 Warning

Hi R-listers, I am trying to do an ANOVA for the following scatterplot and received the following error: library(car) scatterplot(HSuccess ~ Veg, data = data.to.analyze, xlab = "Vegetation border (m)", ylab = "Hatching success (%)") anova(HSuccess ~ Veg, data=data.to.analyze) Error in UseMethod("anova") : no applicable

Hello I've created a 3d scatterplot, and had no problems labeling the points. However, I've been really struggling to change the color of the points based on a factor (see 'group' below). Is such a thing possible? My data look like this: food group x y z apple fruit 0.216 -0.112 -0.893 orange fruit 0.814 0.097 0.460 broccoli veg -0.239 0.240 -0.425 banana

Hello I'm trying to create a barplot with a couple of stacked positive values and with one negative value for each group. example: trees<-c(20,30,10) shrubs<-c(12,23,9) veg<-c(2,3,4) soil<-c(-100,-123,-89) example1<-t(cbind(trees,shrubs,veg)) barplot(example1) #this works so far #but now: example2<-t(cbind(trees,shrubs,veg,soil)) barplot(example2) This shows no more

Hi R-listers, I have developed 47 GLM models with different combinations of interactions from 1 variable to 5 variables. I have manually made each model separately and put them into individual tables (organized by the number of variables) showing the AIC score. I want to compare all of these models. 1) What is the best way to compare various models with unique combinations and different number

o <- (structure(list(sand.silt = structure(list(statistic = structure(185, .Names = "W"), parameter = NULL, p.value = 0.0478835773838087, null.value = structure(0, .Names = "location shift"), alternative = "two.sided", method = "Wilcoxon rank sum test with continuity correction", data.name = ".column by site"), .Names =

Hi R-listers, Q1) What is the difference between the scatterplot and plot function? Q2) I am able to make a graph with the scatterplot function: scatterplot(DevelopIndex ~ Veg, + data = Turtle, + xlab = "Vegetation border (m)", + ylab = "Embryonic development index") And have been successful. But I do not know if the lines are for:

Hi all, Given a data frame as... > head(veg) genus species trophia type geo zone importance 1 Sphagnum subsecundum M A En 100 2 Sphagnum denticulatum M A En 200 3 Molinia caerulea M A En 300 4 Sphagnum flexuosum M A En 400 5 Juncus squarrosus M A En 500 6

I am trying to make some plots for a poster. Each one needs to be 6 inches by inches. Right now the fonts are too small and the plots don't read well on my poster. I am pretty much an R newbie and I can't figure out how to change the fonts. It would also be nice to know how to specify the size of the plot and maybe how to save the plots as jpeg files. Any help would be much appreciated! I

I'm working with the randomForest package and have successfully build a model. I'd like to go one step further however, and use the output from the model to construct a map using the output. My input data are spatial, and I have an independent set of rasterize maps for each of the predictor variables, to map the classification solution. Using the getTree function: >

Hi, I'd like to perform Dufrene-Legendre Indicator Species Analysis for a multivariate regression tree. However I have problems with arguments of duleg(veg,class,numitr=1000)function. How to obtain a vector of numeric class memberships for samples, or a classification object returned from mvpart? thanks in advance -- Best regards, Agnieszka Strzelczak

Dear R help I am having difficulty doing a biplot of the first two factors of a factor analysis. I presume it is because the values in factor 2 for Milk and NUTS are not displayed in the component loadings. Loadings: Factor1 Factor2 RedMeat 0.561 -0.112 WhiteMeat 0.593 -0.432 Eggs 0.839 -0.195 Milk 0.679 Fish 0.300 0.951 Cereals -0.902 -0.267

Hello, I'm trying to calculate non-parametric probabilities using the np package and having some difficulties. OS is Windows, R version 2.11.1 Here is what I've done so far. library(np) veg <- data.frame(factor(Physiogomy), meanAnnualDepthAve, TP) attach(veg) : for clarification dim(veg) returns 1292 3 fy.x <- npcdens(veg$factor.Physiogomy ~ veg$meanAnnualDepthAve, nmulti=1) #

Hello, I tried to post this earlier, but it seems that it did not appear on the list. If you've rec'd 2 m I'm trying to calculate non-parametric probabilities using the np package and having some difficulties. OS is Windows, R version 2.11.1 Here is what I've done so far. library(np) veg <- data.frame(factor(Physiogomy), meanAnnualDepthAve, TP) attach(veg) : for