search for: physiogomy

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 '&quo...

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) # this works, but I haven't found any information explaining what the nmulti=1 term is doing? Does this set the number of levels in...

...er, 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 clarification dim(veg) returns 1292 3 fy.x <- npcdens(veg$factor.Physiogomy ~ veg$meanAnnualDepthAve, nmulti=1) # this works, but I haven't found any information explaining what the nmulti=1 term is doing? Does this set the number of levels in...

...#39;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 row.names(dat) <- paste(row.names(SoilVegHydro$Physiogomy), rep(c(1,2,3), rep(1292, 3)), sep =" ") # following the syntax from the help triangle.plot page this is returned when the last line is submitted. row.names(dat) <- paste(row.names(SoilVegHydro$Physiogomy), rep(c(1,2,3), rep(1292,3)), sep="") Error in `row.names<-.data....

...y 4 terminal nodes, my analysis produces 55 terminal nodes, so unless someone is really interested I'm only using the iris data as an example. This is the model I am sending to ctree. The graph produced is very informative, but I need the information from the plot(Marshct) Marshct <- ctree(Physiogomy ~ meanAnnualDepthAve + meanAnnualDepthWetAve + medAnnualDepthAve + medianAnnualDepthWetAve + medianAnnualDepthDryAve + continHydroWetAve + DCHperiodAverage + DCHydroDryAve + threeDayWaterDepthMinAve + threeDayWaterDepthMaxAve + sevenDayDryFreqAve + sevenDayWaterDepthMaxAve + sevenDayWaterDepthMinAv...

...n probabilities. An example of the graph I'm seeking can be seen here: http://www.statmethods.net/graphs/density.html (scroll to the bottom and examine the Comparing Groups via Kernel Density). A graph (attached) produced using my data: > attach(SoilVegHydro) > vegtype.f <- factor(Physiogomy) > sm.density.compare(meanAnnualDepthAve, vegtype.f, xlab="Mean Annual Depth") # create color fill patterns >colfill <- c(2:(2+length(levels(vegtype.f)))) > legend(locator(1), levels(vegtype.f), fill=colfill) (See attached file: MeanAnnualDepth_Density.png) Thanks...