similar to: Summary

Dear Sirs, I am Professor at Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India. While taking classes, I found the *by() *function producing following error when I use FUN=mean or median and some other functions, however, FUN=summary works. Given below is the output of the example I used on a built-in dataset "mtcars", along with error message reproduced herewith: >

I think you are not using the best function for what your intentions are. Try: > by(data=mtcars, INDICES=list(as.factor(mtcars$am)), FUN=colMeans) : 0 mpg cyl disp hp drat wt qsec vs 17.1473684 6.9473684 290.3789474 160.2631579 3.2863158 3.7688947 18.1831579 0.3684211 am gear carb 0.0000000

Dear All, Thanks for your help. However, I would like to draw your attention to the following: Actually, I was replicating the Example 2.3, using the dataset "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, of a famous book "R by Example" written by "Jim Albert and Maria Rizzo" published in Springers (2012) in a Use R! Series. The

> On Apr 15, 2016, at 1:16 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > Dear All, > > Thanks for your help. However, I would like to draw your attention to the > following: > > Actually, I was replicating the Example 2.3, using the dataset > "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, > of a

I have a binary file(a) with size of (360 720 )for the globe.I wrote the code given below to read and extract an area (south america)from that file. when I use summary for the whole file I got: summary(a, na.rm=FALSE) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.00 1.00 3.00 4.15 7.00 20.00 200083 . But when I used summary for the region(b) which I extracted, I got

Dear All, I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code of their time (2012). Therefore, I have now modified my R-code, as per R-3..2.4 version, according to my requirement

Hello everyone, I am using *mlogit* to analyse my choice experiment data. I have *3 alternatives* for each individual and for each individual I have *9 questions*. I have a response from *516 individuals*. So it is a panel of 9*516 observations. I have arranged the data in long format (it contains 100 columns indicating different variables and identifiers). In mlogit I tried the following

> On Apr 16, 2016, at 2:03 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > Dear All, > > I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code

I suspect the weights argument is not having any effect. Package: Matrix Version: 0.995-2 Date: 2006-01-19 Beginning with this: Browse[1]> resp.lmer <- lmer(SensSSC ~ Block + Season + (1 | Plot) + (1 | Ma) + (1 | Pa) + + (1 | MaPa), weights = SensSSC.N, data = xx) I group the output into a table with my ran.eff function and get this:

I am using R on unix version 63.0 I am doing an image plot of the following data file: ================================ lag1 lag2 cif2d 0.000 0.000 NaN 0.000 1.000 0.500000 0.000 2.000 0.489831 0.000 3.000 0.492986 0.000 4.000 0.493409 0.000 5.000 0.492727 0.000 6.000 0.494485 1.000 0.000 0.500000 1.000 1.000 NaN 1.000 2.000 0.495098 1.000 3.000 0.489831 1.000 4.000 0.492986 1.000 5.000

Hi, I've two questions. Please help me. Thanks! --- Question (1) --- When I type: print("School Name") the output is: [1] "School Name" How to get rid of the '[1]' and the double quotes "" and make the output like this: School Name --- Question (2) --- I got the following output by typing "summary(data)". dstuser dstmethod

This is my first post to R-help and I look forward receiving some advice for a novice like me... I?ve got a simple repeated (4 periods so far) 10-question survey data that is very easy to work on Excel. However, I?d like to move the compilation to R but I?m having some trouble operating on count list data in a neat way. The data C > str(C) 'data.frame': 551 obs. of 13

When I load a table from a data source and run summary() on it, the summary gives me basic summary statistics I'm looking for, and it also discriminates between quantitative and qualitative data and summarizes them accordingly. For example, if I do this: mydata <- read.table("data.txt") summary(mydata) I would get output like this: > summary(mydata) County

Dear list, I reduced my data to the following: x <- c(1,4,2,6,8,3,4,2,4,5,1,3) y <- as.factor(c(2,2,1,1,1,2,2,1,1,2,1,2)) z <- as.factor(c(1,2,2,1,1,2,2,3,3,3,3,3)) I can produce the statistical summary just fine. s1 <- tapply(x, y, summary) d1 <- tapply(x, y, sd) s2 <- tapply(x, z, summary) d2 <- tapply(x, z, sd) First thing: I have 100 plus factors to analyse. Theirs

I was unsure of what suitable goodness-of-fit tests existed in R for logistic regression. After searching the R-help archive I found that using the Design models and resid, could be used to calculate this as follows: d <- datadist(mydataframe) options(datadist = 'd') fit <- lrm(response ~ predictor1 + predictor2..., data=mydataframe, x =T, y=T) resid(fit, 'gof'). I set up a

Hello, I am working from a linux 64 machine on a server with R-2.12 (I can't update to 2.13). I am iterating through many linear mixed models for longitudinal data and I occasionally receive the following convergence error: > BI.lme <- lme(cd4 ~ time + genBI + genBI:time + C1 + C2 + C11 + C12, random =~ 1 + time | IID, data = d) Error in lme.formula(cd4 ~ time + genBI + genBI:time +

I have a case where I would like to change multiple columns containing numbers to factors. I can change each column one at a time as in: TEMP.FACT$EXPOS01<-factor(TEMP.FACT$EXPOS01,levels=c(1,2,3),labels=c("No ne","Low Impact","MedHigh Imp")) TEMP.FACT$EXPOS02<-factor(TEMP.FACT$EXPOS02,levels=c(1,2,3),labels=c("No ne","Low

Hello, I am trying to print a crosttabulation of mean,sd,n for a continuous variable crossclassified by anoother/s grouping variables. I came up with: xtab2 <- function(x,g1,g2) { funy <- function(z) list(mean(z,na.rm=T),sd(z,na.rm=T),length(z)) aa <- by(x,list(g1,g2),funy) bb <- matrix(unlist(aa),nrow=3 ,dimnames=list(c("mean","sd","n"),

Hi guys My data is Tasmania txt There are *N *= 16 samples, consisting of 8 replicate cores (taken from different areas across the sandflat) from each of 2 natural 'treatments' (either disturbed "D" or undisturbed "U" by soldier crab burrowing activity. The abundances of each of *p *= 56 species were recorded from each core (variables 1 to 39 in the file are

Hola Colegas: Me reintegro al estudio de R y quisiera me pudieran resolver el problema que planteo en el archivo adjunto. Gracias anticipadas. *MANOLO MÁRQUEZ P.* ------------ próxima parte ------------ Se ha borrado un adjunto en formato HTML... URL: <https://stat.ethz.ch/pipermail/r-help-es/attachments/20130511/b0c9f15d/attachment.html> ------------ próxima parte ------------ An embedded