similar to: nested, unbalanced anova

I am working with a RCB 2x2x3 ANCOVA, and I have noticed a difference in the calculation of sum of squares in a Type III calculation. Anova output is a follows: > Anova(aov(MSOIL~Forest+Burn*Thin*Moisture+ROCK,data=env3l),type=3) Anova Table (Type III tests) Response: MSOIL Sum Sq Df F value Pr(>F) (Intercept) 22.3682 1 53.2141 3.499e-07 *** Forest

Dear all, In a greenhouse experiment we tested performance of 4 different species (B,H,P,R) under 3 different water levels in 10 replications. As response variable e.g. the number of emerging sprouts were measured on three dates. A simple Anova considering every measurement date separately shows a higly significant effect of species and moisture (and partly the interaction of both). The

I am trying to it a particular nonlinear model common in Soil Science to moisture release data from soil. I have written the function as shown below according to the logist example in Ch8 of Pinheiro & Bates. I am getting the following error (R version 2.1.1) *Error in qr(attr(rhs, "gradient")) : NA/NaN/Inf in foreign function call (arg 1)* Below is the function and data. /#

I have a data.frame paint (below-mentioned). In SPlus I used the command raov( MOISTURE ~ BATCH / PROBE ) (you could do raov( MOISTURE ~ BATCH + PROBE%in%BATCH) as well) so that the factors are taken as random. In R this function raov doesn't exist. How can I calculate the same? Maybe with lme, but how? str(paint) ---------- `data.frame': 60 obs. of 5 variables: $ BATCH : Factor

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

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

Hi everyone, I have a question about calculating r-squared in R. I have tried searching the archives and couldn't find what I was looking for - but apologies if there is somewhere I can find this... I carried out a droughting experiment to test plant competition under limited water. I had: - 7 different levels of watering treatment (1 -7 - from most watered to least watered/) - 15

Hello, I am very new to R but would like to use the software to analyse the attached data. The experiment followed a split-split plot design There were two blocks and the whole plot is CO2 with two levels. The sub-plot is soil temperature with three levels and the sub-sub plot is soil moisture content with three levels (low, intermediate and high-similar for soil temperature). I had 7 plants per

Hello, I am unable to figure out how to code a new column in a data frame based on an existing column that matches a column in a reference data frame, in a relational-db fashion. I would like this to maintain a minimum set of reference tables that may be reused over several similar datasets. Specifically, I have two data frames as listed below, 'Bos' and 'tree.' For each case in

Dear all, I'm analysing a split-plot experiment, where there are sometimes one or two values missing. I realized that if the data is slightly unbalanced, the effect of the subplot-treatment will also appear and be tested against the mainplot-error term. I replicated this with the Oats dataset from Yates (1935), contained in the nlme package, where Variety is on mainplot, and nitro on

Hello, Below is some example code that should reproduce an error I'm encountering while trying to create a tiff plot with two subplots. If I run just the following bit of code through the R GUI the result is what I'd like to have appear in the saved tiff image: x<-seq(0:20) y<-c(1,1,2,2,3,4,5,4,3,6,7,1,1,2,2,3,4,5,4,3,6) plot(x,y,type="l",las=1,ylim=c(0,12))

Hi All: I am working with a dataset on Arsenic toxicity, and I am trying to calculate the 20th, 40th, 60th, 80th, and highest percentiles for a variable, dietary Moisture (variable name dMoist). The inbuilt function quantile(dMoist) would print 0, 25th, 50th, 75th, and 100th percentile. Does there exist a function that can calculate xth percentile (where x = 10th, 20th, ... etc) values?

Hi, I want to know the area under a curve, which is not given as a function, but as values in a time series. It is not a smooth curve, but switches often between positive values and zero (the values describe the moisture in the soil over a year, one entry is one day). I already tried area.between.curves, but got only 0 as result. I guess, it doesn't work because of these multiple changes

Hi, For my master thesis I have 24 micro-plots on which I did measurements during 3 months. The measurements were: - Rainfall and runoff events throughout 3monts (runoff being dependant on the rainfall, a coefficient (%) has been made per rainfall event and per 3 months) - Soil texture (3 different textures were differentiated) - Slope (3 classes of slopes) - Stoniness (one time measurement)

I have created a scatter plot that has come out okay but I am having trouble with the x axis. My data consists of 4 treatments but these treatments are days so R keeps reading them as numeric and making my x axis continuous. Here is what I have so far: plot(pair$MC~pair$Day, pch=c(19,24)[as.factor(Cookie)], main='Paired t Test', xlab='Days in Field', ylab='Moisture

I have nc files for global soil moisture,here is one file https://echange-fichiers.inra.fr/get?k=f9DDllPKdUKs5ZNQwfq from the metadata ,the projection is cylindrical and the resolution is 25 km(it is based on authalic sphere based on International 1924 ellipsoid).As I want to compare with other data, I have to make them identical. - my other data are in WGS84 with 0.25*0.25 degree resolution

Hi, I have modified the USJudgeRatings data (available in R) to illustrate my question. # Use the first 4 variables of USJudgeRatings and add a group variable with two levels USJudgeRatings <- USJudgeRatings[,1:4] USJudgeRatings$group <- factor(c(rep(1, 22), rep(0, 21))) # I can draw a pairs graph where members of each group are drawn in different colors: pairs(USJudgeRatings[,1:4], col

Paul, I was trying to make a minimal self contained example, but I guess I went too far on the minimizing. The original problem came from code more like: library(TeachingDemos) hist(rexp(1000), main='') abline( v=1, col='red') sp.par <- subplot(hist(rnorm(100), main=''), x='topright') op <- par(sp.par[c('usr', 'plt')]) abline(v=0,

I would like to calculate the mean of tree leader increment growth over 5 years (I1 through I5) where each tree is a row and each row has 5 columns. So far I have achieved this using rowMeans when all columns are numeric type and used in the calculation: Data1 <- data.frame(cbind(I1 = 3, I2 = c(0,3:1, 2:5,NA), I3 =c(1:4,NA,5:2),I4=2,I5=3)) Data1 Data1$mean_5 <- rowMeans(Data1, na.rm =T)

In lattice #toy data library(ggplot2) library(lattice) x <- rnorm(100) y <- rnorm(100) k <- sample(c("Weak","Strong"),100,replace=T) j <- sample(c("Tall","Short"),100,replace=T) w <- data.frame(x,y,j,k) xyplot(y~x|j+k,scales=list(y=list(relation="free"))) will give you a scale in each subplot with a range equal to the range of y