similar to: Add Anova statistics in each figure

Hi, I am trying to find m breakpoints of a linear regression model. I used the segmented package. It works fine for small number of predicators and breakpoints.(3 r.v. 3 points). However, my model has 14 variables it even would not work even for just one breakpoints!. The error message is always estimated breakpoints are out of range. Since my problem is time related problem. So I

Hi all, Hope you people do not feel irritated for repeatedly sending mail on Time series. Here I got another problem on the same, and hope I would get some answer from you. I have following dataset: data[,1] [1] 4.96 4.95 4.96 4.96 4.97 4.97 4.97 4.97 4.97 4.98 4.98 4.98 4.98 4.98 4.99 4.99 5.00 5.01 [19] 5.01 5.00 5.01 5.01 5.01 5.01 5.02 5.01 5.02 5.02 5.03 5.03 5.03

Hello, Two lapply questions (system info and sample data below): 1) Why does the first form of command1 add the name of y _after_ the str() output rather than before as does the second (preferred) form? # command1 version1 invisible(lapply(ls(pattern='bn'), function(y) cat(y, "\n", str(get(y)), "\n") )) # command1 version2 (preferred output)

Hi nice people, i am trying to made a double "for" cycle, i wish that for cycle on k activates t times the for cycle on s the first cycle is this: s<-rep(1,10) s [1] 1 1 1 1 1 1 1 1 1 1 > for (n in 2:10) { + s[n]=1+s[n]+rnorm(1,mean=0,sd=1) + } > s [1] 1 4.75 4.86 4.05 4.09 4.56 4.63 4.65 4.12 4.01 now i wish another cycle that activates t times the before cycle gives

Hi all, I have this problem with lattice that xyplot() won't draw some of my axis labels if the type (i.e. the relation argument) of scales is set as free. For example, in the plot below, I would want it to also show: 1. the labels E1,...E6 below the 10th panel (i.e. 3rd row, 2 col)....just as it is now done below the 12th panel.... 2. as well as the labels (2,4,6,8) on the top of panels 1

Hi, Currently object.size() is not very useful on environments as it always returns 56 bytes, no matter how big the environment is: env1 <- new.env() object.size(env1) # 56 bytes env2 <- new.env(hash=TRUE, size=75000000L) object.size(env2) # 56 bytes env3 <- list2env(list(a=runif(25000000), L=LETTERS)) object.size(env3) # 56 bytes This makes it pretty useless on

Hi all, I'm searching for a little clarification on partial mantel tests (ecodist package) I've a distance matrix (x,y), and several others containing environmental/chemical variables. Based on the help file, and the package instructions I've managed to implement the tests as; var1 ~ env1 + space to partial out the effect of space and test the relationship between the

Dear R Users,i am very new to R. I want your help on an issue regarding distance matrix and cluster analysis i had discharge data of 4 rivers(a,b,c,d) in 4 vectors each having 364 values > dput(qmu)structure(list(a = c(0.26, 0.25, 0.25, 0.25, 0.24, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.19, 0.19, 0.19, 0.19, 0.18, 0.18, 0.18, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17, 0.17,

Hello, I'm trying to illustrate the relationships between various trait and environment data gathered from a number of sites. I've created a GAM to do this: gam1=gam(trait~s(env1)+s(env2)+te(env1,env2)) and I know how to create a 3D plot using vis.gam. I want to be able to show points on the 3D plot indicating the sites that the data came from. I can do this on a 2D plot when there is one

Hi Gabe, On 09/29/2015 02:51 PM, Gabriel Becker wrote: > Herve, > > The problem then would be that for A a refClass whose fields take up N > bytes (in the sense that you mean), if we do > > B <- A > > A and B would look like the BOTH take up N bytes, for a total of 2N, > whereas AFAIK R would only be using ~ N + 2*56 bytes, right? Yes, but that's still a *much*

I am running into a problem with my LDAP puppet setup with this error message: PuppetClient: err: Could not retrieve catalog from remote server: Error 400 on SERVER: Could not parse for environment DR: undefined method `to_sym'' for ["ENV1", "ENV2"]:Array PuppetMaster: err: Could not parse for environment DR: undefined method `to_sym'' for ["ENV1",

Hi folks, Where can I find document re "how to read anova output"? Google found many of them. But seemingly non of them can explain to me following output:- > tabA = c(5.67, 5.67, 5.55, 5.57) > tabB = c(5.75, 5.47, 5.43, 5.45) > tabC = c(4.74, 4.45, 4.65, 4.94) > tabs = data.frame(tabA, tabB, tabC) > tablets = stack(tabs) > anova(lm(values ~ ind, data =

Hi everyone, I'm looking to produce a side-by-side histogram of the number of trips taken by jays with a particular number of acorns after accounting for year (year "one" and year "two"). I know this involves indexing first then creating a histogram but I'm not sure how I'd do this. I want to explore the possibilities that jays are altering their strategies in

Dear R Group I have the following data for which I am trying to create subject wise lattice plot for a given attribute and product . though the lattice plot is generated, for some reasons that i dont understand in each plot the subject panels take a random order, I would rather want all the plots to display the subject order in the same order as how i have ordered this particular factor level.

Hi - I am interested in solving variance components for the data below with respect to the response variable, Expression within R. However, the covariates aren't independent and they also have a class (of which the total variance explained by covariates in that class I am most interested in). Very naively, I have tried to look at each individual covariates variance like this >

I'm creating a lattice barchart based off a pretty complicated data structure. The barchart comes out quite nice ( thanks to lattice ) but the problem is that the horizontal axis comes out all scrunched because the barchart doesn't know that the intervals of Var.1 are really "associated" with the conditioning variable Var.2. Therefore, all the intervals of Var.1 are put on

Both of the approx functions work correctly individually, but they are not being distinguished in the for loop by the if statments. Any help would be appreciated. for loop of interest is below x <- (structure(list(Site = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,

I would like to preform a t.test to each of the measured variables (sand.silt etc.) with a mean and sd for each of the treatments (up or down), and out put this as a table.... I am having a hard time starting- maybe it is to close to lunch. Any suggestions would be greatly appreciated. Stephen Sefick x <- (structure(list(sample. = structure(c(1L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 2L, 3L,

Dear all, I am facing some problem with how to fit a "Baseline category Logit model" with R. Basically I am considering famous "Alligator" data as discussed by Agresti. This data can also be found here: https://onlinecourses.science.psu.edu/stat504/node/174 (there is also an accompanying R file, however the underlying R code could not load the data properly!!!) Below are

OK, so maybe last night was a little too much at one throw, so I have reduced the data to two stations- one that has precipitation and one that does not. This is going to be in the context of a larger data set. I would like to be able to issue a ggplot command and have cum sum just act on the facets (factors) to apply this. library(chron) library(ggplot2) DF <- structure(list(date_time =