similar to: problem coercing truncated character vector to levels

I'm trying to use tapply to output means and SD or SE for my data but seem to be limited by how many times I can subset it. Here's a snippet of my data > stems353[1:10,] Time DataSource Plot Elevation Aspect Slope Type Species SizeClass Stems 1 Modern Cameron 70F221 1730 ESE 20 Conifer ABCO Class1 3 2 Modern Cameron 70F221 1730

Hi list, This is a very basic question about lattice: I wish to add some vertical lines in each panel of a xyplot as demonstrated in this example: > library(lattice) > > xx <- seq(1, 10, length=100) > x <- rep(xx, 4) > y <- c(cos(xx), sin(xx), xx, xx^2/10) > fact <- factor(rep(c("cos", "sin", "id", "square"), each=100))

I am using R to make two-way ANOVA on a number of variables using g <- aov(var ~ fact1*fact2) where var is a matrix containing the variables. However the outcome seem to be dependent on the order of fact1 and fact2 (i.e. fact2*fact1) gives a slightly (factor of 1.5) different result. Any ideas why this is? Thanks for any help Anders

Dear list, I've been trying this for a few hours and I just don't understand how lattice works with groups and subscripts. Consider the following example, > xx <- seq(1, 10, length=100) > x <- rep(xx, 4) > y <- c(cos(xx), sin(xx), xx, xx^2/10) > fact <- factor(rep(c("cos", "sin", "id", "square"), each=100)) > fact2

I am trying to construct a two-way table where, instead of printing the two-way frequencies in the table, I would like to print the values of a third variable that correspond to the frequencies. For example, the following is easily constructed in R > fact1 <- factor(sample(LETTERS[1:3],10,replace=TRUE)) > fact2 <- factor(sample(LETTERS[25:26],10,replace=TRUE)) > fact3

Dear R-users, consider the two following outputs, ## 1 and ## 2 \begin{Scode}{Setup, echo = FALSE, print = FALSE, eval = TRUE} with(expand.grid(Fact1 = 1:3, Fact2 = 1:40), table(Fact1, Fact2)) ## 1 xtable(with(expand.grid(Fact1 = 1:3, Fact2 = 1:40), table(Fact1, Fact2))) ## 2 \end{Scode} The first line with(expand.grid(Fact1 = 1:3, Fact2 = 1:40), table(Fact1, Fact2))

Dear ExpeRts, Suppose I have a typical psychological experiment that is a within-subjects design with multiple crossed variables and a continuous response variable. Subjects are considered a random effect. So I could model > aov1 <- aov(resp~fact1*fact2+Error(subj/(fact1*fact2)) However, this only holds for orthogonal designs with equal numbers of observation and no missing values.

In my undertstanding of the problem, the model lme1 <- lme(resp~fact1*fact2, random=~1|subj) should be ok, providing that variances are homogenous both between & within subjects. The function will sort out which factors & interactions are to be compared within subjects, & which between subjects. The problem with df's arises (for lme() in nlme, but not in lme4), when

Hello, I am a new user or R, and am so far very impressed with its capabilities. However, I have no programming experience, and am having some issues in trying to tell the software what I want done. There are basically two issues which I am currently grappling with. The first, I have a data matrix, with two factors and dozens of response variables. I am interested on conducting ANOVAs on

Dear all, The following example code produces a graph with ggplot2, to which I add several vertical lines of arbitrary colors. I am not satisfied with the legend: it automatically adds some vertical lines which I'd rather not see (they confuse the reader rather than add information in this case). > library(ggplot2) > dfr <- data.frame(values = sin(1:50/10), > fact =

Dear r-help, With lme, is there a way to specify multiple fixed factors under one level of grouping? For example, for a single fixed factor, I use the following: fm1.lme <- lme(fixed=resp ~ fact1, random=~1|subj/fact1, data=mydata) I would like to have multiple factors under subj, like the following for a two-way design, but I get an error: fm2.lme <- lme(fixed=resp ~ fact1*fact2,

I am trying to put 3 dotcharts side-by-side with minimal space between each. Each chart is for a different variable, but the vertical axes are the same. I want to have vertical axis labels on the lefthand chart but no vertical axis labels on the other two. Plus, I would like very little space between charts 1 & 2 and between charts 2 & 3. I have one approach but am not too happy with

Hello all, I have some trouble in reconstructing a valid expression within a function, here is my question. I am building a function : SUB<-function(DF,subset=TRUE) { #where DF is a data frame, with Var1, Var2, Fact1, Fact2, Fact3 #and subset would be an expression, eg. Fact3 == 1 #in a first time I want to build a subset from DF #I managed to, with an expression like eg. DF$Fact3, # but I

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

Hello to all users and wizards. I am regulary using 'boxplot' function or its analogue - 'bwplot' from the 'lattice' library. But they are, as far as I understand, totally flawed in functionality: they miss ability to select what they would draw 'in the middle' - median, mean. What the box means - standard error, 90% or something else. What the whiskers mean -

I wantto run sequential ANOVAs (i.e. type I sums of squares), and trying to getresults including ANOVA tables and associated coefficients for predictive variables(I am using the R 3.4.2 version). I think ANOVA tables look right, but believecoefficients are wrong. Specifically, it looks like that the coefficients arefrom ANOVA with ?marginal? (type III sums of squares). I have tried both lme

The message for aov1 was "Estimated effects <may> be unbalanced". The effects are not unbalanced. The design is 'orthogonal'. The problem is that there are not enough degrees of freedom to estimate all those error terms. If you change the model to: aov1 <- aov(RT~fact1*fact2*fact3+Error(sub/(fact1+fact2+fact3)),data=myData) or to aov2 <-

Is there any way to put an argument into an object name. For example, say I have 5 objects, model1, model2, model3, model4 and model5. I would like to make a vector of the r.squares from each model by code such as this: rsq <- summary(model1)$r.squared for(i in 2:5){ rsq <- c(rsq, summary(model%i%)$r.squared) } So I assign the first value to rsq then cycle through models 2 through

I have used foreach() for parallel computing but in the current problem, it is not working. Given the volume and type of the data involved in the analysis, I will try to give below the complete code without reproducible example. In short, each R environment will draw a set of separate files, perform the analysis and dump in separate folders. splist <- c("juoc", "juos",

Does anyone know of any issues with nesting source() calls within multiple scripts? I have at least one script which always finds errors when I source it but runs fine when run on its own. It containd source() calls to other scripts and it seems to fail during the first nested source() command. Ken Kenneth B. Pierce Jr. Research Ecologist Landscape Ecology, Modeling, Mapping and Analysis