similar to: extracting elements from summary(aov object)

I'm using Samba 3.0.3 on Fedora Core 2 with OpenLDAP 2.1.29 for a backend. I'm getting to typical "The user name could not be found." error upon trying to join a Windows box. I've gone through every digest on lists.samba.org and other sites and nothing has worked yet. Any suggestions: Here's what I've done so far: 1. Installed everything via RPMS: [root@smbtest

Greetings, After pouring over the documentation for the 'colorspace' package, I have not been able to figure out how the plot() method converts colorspace coordinates to RGB values for display on the screen. I am convert between colorspaces with the various as() methods... but cannot seem to find a way to extract RGB (i.e. for displaying on a computer screen) triplets from color space

After, oh, six months of attempts here and there to read everyone's experiences with Samba/LDAP and inability for a windows 2000/XP machine to join the domain, I finally discovered what was not working properly. In my smb.conf I put: add machine script = /usr/local/sbin/smbldap-useradd -w "%u" As instructed by many How-to's and Idealx. However, I thought to myself, %m

Hi, forgive me if someone has already posted about this but I have had a look and cannot find the answer, also I am very new to R and been getting the grips with this. I have been trying to use Adonis to find out if there are significant difference between groups on data that I have analyses with NMDS, and have been struggling with getting this to work and understanding what is going on. I am

Dear all; First of all, this is probably a more conceptual question than a R-related one, but still want to give it a try. When working with the interpolation function "interp" from the package akima and the triangulation function "tri.mesh" from package tripack I've got NA's for the interpolation and "error" for the triangulation. The data is arranged in a

Hi, every body! I am a new comer for R, so my question would unavoidablely sounds stupid. Sorry! In my experiment, there are two type of soil ( soil F and soil D), each half of them were subjected to steam sterilize (result in FS and DS soil). A equal volume of soil from two of the four soil types (F, D, FS, DS) were mixed as follows: F+F, F+D, F+FS, F+DS, D+F, D+FS, D+DS, FS+DS (eight

Is there a way to prevent the re-ordering of factors by aov? I do have a three-way interaction that I do want to fit before a two-way interaction (different factors, so they are not nested), but R moves the two-way interaction to the front. I know it generally makes sense to fit the two-way interactions first, but in this case I think I know what I'm doing. + hv

Hello Trying to develop variograms and kriged surfaces from a point file. Here is what I've done so far. library(gstat) # also loads library(sp) library(lattice) soilpts$x <- soilpts$UTM_X soilpts$y <- soilpts$UTM_Y soil.dat <- subset(soilpts, select=c(x, y, Area, BulkDensity, LOI, TP, TN, TC, Total_Mg)) dim(soil.dat) [1] 1292 7 coordinates(soil.dat) <- ~ x+y

Dear R community, I am using xYplot() from the Hmisc package. The package works great to plot means + CI. But I am having issues handling the scales. I am plotting "Soil Clay content" vs "Soil depth" by "land use". Usually in this type of graphs it is better to place the variable "soil depth" in the y-axis and it should be ordered downward by depth (0-5

Dear all, I've used glm(family=binomial(link="logit")) several times, but now I think that a log link is more appropriate. I want to fit a model for probability of tree fall (TF)), with tree diameter (dbh) and soil moisure (soil) as predictors. A large number of trees have been checked every second year whether they stand up (0) or have fallen (1). I assume that the tree fall

Hi I have a netCDF file of volumetric soil water content at four different soil layers and want to convert each soil layer in the netCDF file to a GeoTIFF layer. This code converts the netCDF file to one GeoTIFF layer, i.e. unclear which soil depth. file.nc <- "C:/Soil_Weather_data/Agro/VMC21/VMC21.nc" file.tiff <- "C:/Soil_Weather_data/Agro /VMC21/VMC21" importnetcdf

Hello I am trying to fit a REML to some soil mineral data which has been collected over the time period 1999 - 2004. I want to know if the 19 different treatments imposed, differ in terms of their soil mineral content. A tree model of the data has shown differences between the treatments can be attributed to the Magnesium, Potassium and organic matter content of the soil, with Magnesium being the

Hi Ahmed, When reading from a ncdf file you can use the 'varname', 'lvar' and 'level' arguments - see the 'Details' section in the docs https://www.rdocumentation.org/packages/raster/versions/2.6-7/topics/raster <https://www.rdocumentation.org/packages/raster/versions/2.6-7/topics/raster> We can't tell what is in the ncdf file from what you report other

All, I'm trying to analyze the results of a reciprocal transplant experiment using lme(). While I get the error-term right in aov(), in lme() it appears impossible to get as expected. I would be greatful for any help. My experiment aimed to identify whether two fixed factors (habitat type and soil type) affect the development of plants. I took soil from six random sites each of two types

Hello all R listers, I'm struggling to select an appropriate statistical method for my data set. I have collected soil moisture measurements every hour for 2 years. There are 75 sensors taking these automated measurements, spread evenly across 4 treatments and a control. I'm not interested in being able to predict soil future soil moisture trends, but rather in knowing whether the

RSiteSearch("creating datasets", restrict="doc") gives me R-exts.html as the first hit... I did pretty much the same thing you did and had no problem. In the data/ directory of the source package I only have the one .rda file and nothing else. Did you try installing the package and test it before you run check? Andy > From: Jim Lemon > > Hi folks, > >

Hi All, I am trying to lable the y-axis on my scatterplot with the following: "Soil moisture content (m3m-3)" I am using the following coding for plotting the graph: plot(soilmoisture~gradientlevel, xlab="Levels of droughting gradient", ylab="Soil moisture content (m3m-3)", bty="l", font.main="2", pch=16, las=1, cex.lab="1.13") I have

Dear All, I'm trying to save a dataframe using write.table command. It works, but when I retrieved, there's an error message as shown below: > write.table(soil.dat,file="C:/soil.rdata") > load("C:/soil.rdata") Error: bad restore file magic number (file may be corrupted)-- no data loaded I can figure out the error message. Any assistance to solve the

Greetings, I have a groupedData (nmGroupedData) object created with the following syntax: Soil <- groupedData( ksat ~ conc | soil_id/sar/rep, data=soil.data, labels=list(x='Solution Concentration', y='Saturated Hydraulic Conductivity'), units=list(x='(cmol_c)', y='(cm/s)') ) the original data represents longitudinal observations in the form of:

Greetings, A couple general questions regarding the use of splines to interpolate depth profile data. Here is an example of a set of depths, with associated attributes for a given soil profile, along with a function for calculating midpoints from a set of soil horizon boundaries: #calculate midpoints: mid <- function(x) { for( i in 1:length(x)) { if( i > 1) { a[i] = (x[i] -