similar to: Help writing basic loop

Hello, R users, I applied segmented regression method contributed by Muggeo and got different slope estimates depending on the initial break points. The results are listed below and I'd like to know what is a reasonable approach handling this kinds of problem. I think applying various initial break points is certainly not a efficient approach. Is there any other methods to deal with segmented

Evening folks, I'm trying to print a series of graphs to .jpeg using a variable as the title, but run into the difficultly that I can't find a way to append the file extension to the .jpeg (in this case extensionless!) files. Example: ---- species.name="CussoniaHolstii" dia<-10:100 biomass = -21.4863 + 0.5797 * (dia ^ 2) biomass jpeg(species.name) plot (biomass,

Hi -- I had a pretty quick R question since unfortunately I have not been able to find an answer on Google. It shouldn't take much more than a minute to answer. I'm trying to add up the major gleason grade and minor gleason grade for an analysis of patients with prostate cancer. One column has values under "Major Gleason" and another column has values under "Minor

This isn't a question about R, but I'm hoping someone will be willing to help. I've been looking at calibration plots in multiple regression (plotting observed response Y on the vertical axis versus predicted response [Y hat] on the horizontal axis). According to Frank Harrell's "Regression Modeling Strategies" book (pp. 61-63), when making such a plot on new data

I know citation() gives the R citation to be used in publications. Has anyone put this into endnote nicely? I'm not very experienced with endnote, and the way I have it at the momeny the 'R Development Core Team' becomes R. D. C. T. etc. Cheers.

Dear list, I want to create a POSIX time vector as follows: day <- as.character("110809") time.t <- 1:3600 t.min <- time.t %/% 60 t.sec <- time.t-t.min*60 DATE <- as.POSIXct(strptime(paste(day,t.min,t.sec),"%y%m%d %M%S")) Tail(DATE) The problem is that the last element (3600) returns a NA and I don't understand why. 600, 1200, 2400

Dear all, I would like to ask you if R can produce any kind of sound. It would be useful when code execution stops R to notify me by playing some sound. Is that possible in R? I would like to thank you in advance for your help Best Regards Alex

Hello R-Users, it might be a rather simple problem I have, but I couldn't find any solution online. Thus, here is my problem: I would like to adjust the y-axis range in a barplot, since all my values are >70. Therefore I would like to only visualize the y-axis from 60-100 (example 1). The problem is, the range of the y-axis is adjusted, but the barsize stays the same and vanishes from

Dear, i am a student and I need help in comparing between different slopes and finding whther there is a significant difference between them? Thanks a lot [[alternative HTML version deleted]]

Dear R users, i'm using a custom function to fit ancova models to a dataset. The data are divided into 12 groups, with one dependent variable and one covariate. When plotting the data, i'd like to add separate regression lines for each group (so, 12 lines, each with their respective individual slopes). My 'model1' uses the group*covariate interaction term, and so the coefficients

Hello R users, I've used the following help two compare two regression line slopes. Wanted to test if they differ significantly: Hi, I've made a research about how to compare two regression line slopes (of y versus x for 2 groups, "group" being a factor ) using R. I knew the method based on the following statement : t = (b1 - b2) / sb1,b2 where b1 and b2 are the two slope

Dear R Community, I am new to R, and have a question that I suspect may be quite simple but is proving a formidable roadblock for me. I have a large data set that includes water-quality measurements collected over many 24-hour periods. The date and time of sample collection are in a combined Date/Time field in the format yyyy-mm-dd hh:mm:ss. I need to be able to subset the data for analysis of

Hi R-Help! My question: I have lifetime/failure data of machines with different stress levels and i think an weibull/extreme value distribution would fit this data. So I did: model1 <- survreg(Surv(lfailure)~stress,data=steel,dist="extreme") (where lfailure=log(failure)) Now I would like to do a likelihood ratio test to test the hypothesis H0: location parameters of the

Dear Helpers, I just started working with R and I'm a bit overloaded with information. My data is from marsupials reindroduced in a area. I have weight(wt), hind foot lenghts(pes) as continues variables and origin and gender as categorial. condition is just the residuals i took from the model. > names(dat1) [1] "wt" "pes" "origin" "gender"

Dear List: First, many thanks to those who offered assistance while I constructed code for the simulation. I think I now have code that resolves most of the issues I encountered with memory. While the code works perfectly for smallish datasets with small sample sizes, it arouses a windows-based error with samples of 5,000 and 250 datasets. The error is a dialogue box with the following: "R

R offers a bewildering array of options when it comes to representing dates and times (e.g, as.Date, chron, strptime, zoo, etc). Can anybody recommend a document that compares the relative merit of each method? I'm not looking for help with any one method, but rather a guide that describes which method is best for a particular data analysis/plotting goal. Thanks, Jake [[alternative

Hi guys, Got a few days left and I need to model a random effect of species on the body mass (logM) and temperature (K) slopes. This is what i've done so far that works: model1<-lme(logSSP~logM + K,random=~1|species,data=data1) model2<-lme(logSSP~logM + K,random=~K|species,data=data1) model3<-lme(logSSP~logM + K,random=~logM|species,data=data1) The one I now want is:

Hi, I'm fitting a glm to a dataset... > objects() [1] "pop.div.full" "speciation.data" ...and then performing model simplification to give a series of model objects all of which have a common suffix. > objects() [1] "pop.div.full" "pop.div.gp.f.b.hm" [3] "pop.div.gp.fb.hm"

Hi, I am trying a linear regression model where the dependent variable is the size of the heart corrected for the patient's height and weight. This is labelled as LAVI. The independent variables are race (european or non-eurpoean), age, sex (male or female) of the patient and whether they have diabetes and high blood pressure. sample size 2000 patients selected from a community. when I

Dear R-helpers, I'm trying to associate linear coefficients (intercept and slope) to tens of thousands of observations based on a table with benchmark values. #####Example - Value table and their corresponding coefficients (intercept and slope) coef = data.frame(cbind(st=c(1:5),b = runif(5,0.3,5),a = seq(0.5,5,1)))print(coef) #Example of observations to be computedobs = runif(20,1,5)print(obs)