search for: physiogomi

Hello, vegMeans <- by(SoilVegHydro[3:37] , SoilVegHydro$Physiogomy, mean) vegSD <- by(SoilVegHydro[3:37] , SoilVegHydro$Physiogomy, sd) write.table(vegMeans, file="A:\\Work_Area\\Steve\\Hydrology_Data\\data\\vegMeans.txt") Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : cannot coerce class '"by"' into a

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

hello, I am trying to develop a triangle plot but am having difficultly assigning the row.names to the 3 columns in the data.frame Here is what I've done, attach(SoilVegHydro) dim(SoilVegHydro) 1292 39 # now take 3 variables from main data.frame for plotting dat <- cbind.data.frame(TP, meanAnnualDepthAve, BulkDensity) # These are variables held in the data frame SoilVegHydro

Hello, This is a re-submittal of question I submitted last week, but haven't rec'd any responses. I need to extract the probabilities used to construct the barplots displayed as part of the graph produced by plot("ctree"). For example, library(party) iris.ct <- ctree(Species ~ . , data = iris) plot(iris.ct) Instead of a simple example with only 4 terminal nodes, my

Hello, I would like to produce a series of graphs comparing the probability distributions for 8 factors against a continuous metric. The kind of graph I'm hoping to produce would look like the density comparison graphs (library sm) using the function sm.density.compare. However, instead of calculating the density distributions for comparisons, I'd like this comparison to be based on