search for: shrubcover

...ames(TotalCover.df)<- c("Station","Shrub","Tree","Invasive","Herb","Litter","Bare") Shrub.df<-data.df[data.df$Layer=="Shrub",] Tree.df<-data.df[data.df$Layer=="Tree",] Cover.fn<-function(ID){ ShrubCover.df<-Shrub.df[Shrub.df$Quadrat==ID,] for (j in 1:length(ShrubCover.df[,"Quadrat"])){ for (i in 1:751){ if (TotalCover.df[i,"Station"]>=ShrubCover.df[j,"Start"] && TotalCover.df[i,"Station"]<= ShrubCover.d...

...es(TotalCover.df)<- c("Station","Shrub","Tree","Invasive","Herb","Litter","Bare") Shrub.df<-data.df[data.df$Layer=="Shrub",] Tree.df<-data.df[data.df$Layer=="Tree",] Cover.fn<-function(ID){ ShrubCover.df<-Shrub.df[Shrub.df$Quadrat==ID,] for (j in 1:length(ShrubCover.df[,"Quadrat"])){ for (i in 1:751){ if (TotalCover.df[i,"Station"]>=ShrubCover.df[j,"Start"] && TotalCover.df[i,"Station"]<= ShrubCover.d...

Hi, I would like to conduct a MANOVA. I know that there 's the manova() funciton and the summary.manova() function to get the appropriate summary of test statistics. I just don't manage to specify my model in the manova() call. How to specify a model with multiple responses and one explanatory factor? If I type:

Hi, I have done different discriminant function analysis of multivariat data. With the CV=True option I was not able to perform the predict() call. What do I have to do? Or is there no possibility at all? You also need the predicted values to produce a plot of the analysis, as far as I know. Here my code: pcor.lda2<-lda(pcor~habarea+hcom+isol+flowcov+herbh+inclin+windprot+shrubcov+baregr,

Dear R Help, I am having difficulty using Variogram within GLS to examine spatial structure of nested data. My data frame consists of ecological measurements of a forest, in which three landscape positions ("landposi") are compared. Each landscape position is replicated five times ("replicat"), and the environment is measured ("canopy", "litdepth", etc.)