similar to: many chr2factors ?

Hello :) I have two data frames, one has properties taken on a piece by piece basis and the other has performance on a lot by lot basis. I wish to combine these two data frames but the problem is that each lot has multiple pieces and hence i need to take a mean of the properties of multiple pieces and match it to the row having data about the lot. I was wondering if there is a simple commmand,

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Hello all, I have read as many merge issues as I possibly could tonight and although I presume this is a small error, I have not found the solution to my problem. I'm trying to merge two data sets: dat0 and TransTable. As you can see below, dat0 has 8000 rows, whereas TransTable has 47296 rows. I would expect when I merge the two data sets, with all.x=F, and all.y=F, that the

Hi, is there a exstisting function (..i found nothing until now.) what makes it possible transfrom a dataset: ID AGE V.MAI V.JUNE 11 20 100 120 12 30 200 90 into ID AGE V 11 20 100 11 20 120 12 30 200 12 30 90 ,or have i to programm ths my self? Thanks for any comment, help and/or starting point. regards,christian

Hi, I have a data set (weight) that does not follow the Gaussian (Normal) distribution. However, I have to transform the data before applying the Gaussian distribution. I used this syntax and used log(weight) as: posJy.model<-glm(log(weight) ~ factor(pos), family=gaussian(link='identity'), subset=Soil=="Jy"). This syntax COULD NOT transform the data. But if I transform the

Hi, all, I used lxc-tools to create a linux container. I am trying to transfrom LXC container configuration into a domain XML fragment using the following command: *$ virsh -c lxc:/// domxml-from-native lxc /var/lib/lxc/my_conatiner/config* However, I get the error message, error: this function is not supported by the connection driver: virConnectDomainXMLFromNative It seems that

I want to transform the data by "tapply" to one dataframe. But I can not get it. For example: > tst=tapply(point,pp,length) > tst[1:10] p1 p10 p100 p1000 p1001 p1002 p1003 p1004 p1005 p1006 1 5 1 8 6 5 8 7 4 4 > res=as.data.frame(tst) # I try to transform it > res[1:10,] p1 p10 p100 p1000 p1001 p1002 p1003 p1004 p1005 p1006 1 5 1 8 6 5

Hello all, Would somebody be kind enough to show me how to do a KS test in R for a lognormal distribution with ESTIMATED parameters. The R function ks.test()says "the parameters specified must be prespecified and not estimated from the data" Is there a way to correct this when one uses estimated data? Regards, Kwabena. -------------------------------------------- Kwabena Adusei-Poku

Hi I just started using RGui.exe under widnows. I have a text file containing date arranged in columns and rows, each column has the same format, each row with different formats. 3 of the columns are something like this 1/12/2006 3:59:45 PM I need to calculate the different in seconds between 2 selected periods using their row’s index My solution: Read the file in a data frame and

Hi ether, On 12/26/09 13:06, ether zhhb wrote: > hi, > > dose anyone going/planning to add something like > Graphite(http://gcc.gnu.org/wiki/Graphite) in gcc to llvm(or that > should be implement at the level of clang?)? I already looked into implementing something like Graphite for LLVM. However just recently, so I have not released any code yet. As soon as some code is

Dear R-core There is a different output for the apply function due to the change of unlist as mentioned in the R news. Newly, applying as.factor() (or factor()) in str(dat <- data.frame(x = 1:10, f1 = gl(2,5,labels = c("A", "B")))) (d1 <- apply(dat,2,as.factor)) newly returns a character matrix while in R-2.3.1 the same command resulted in an integer matrix that was

Hello everbody, i'm currently using the anova()-test for a small data.frame of 40 rows and 2 columns. It works well, but is there any preconditions for a valid variance analysis, that i should consider? Thank you for your answer, Daniel

Dear R-list I have a question concerning the argument "adjustSigma" in the function "lme" of the package "nlme". The help page says: "the residual standard error is multiplied by sqrt(nobs/(nobs - npar)), converting it to a REML-like estimate." Having a look into the code I found: stdFixed <- sqrt(diag(as.matrix(object$varFix))) if (object$method

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

I have some doubts about the validity of my procedure to estimeate linear contrasts ina a factorial design. For sake of semplicity, let's imagine a one way ANOVA with three levels. I am interested to test the significance of the difference between the first and third level (called here contrast C1) and between the first and the seconda level (called here contrast C2). I used the following

hi all, I wish to draw on the same graphic device 3 functions. But i don't want them to be on different graph, i want to compare them on the same I don't need mfrow or mfcol, I need something else... 1 graph on 1 device inside this graph 3 ploted function. I saw something unsing data.frame, but i think it's overkill, and something less complicated must exist, if not why? why not

Hello Could you please suggest a way to find out the r square values for each independent variable while using "lm" for developing a multiple linear regression model. Thank you avneet "I have no data yet. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories instead of theories to suit facts." ~ Sir Arthur Conan Doyle

Hi In mixed-model with lme() How can I obtain Type II SS or Type III SS for fixed effect? Thanks Julien

Hi, I'm studying math, and i have to make an analysys using Randomised Block Design. I have two factors, i know how to do this in Statistica, but how to do this in R, i read some manuals but the only thing that i have found was 2 factor ANOVA. Please could someone help me, or give some usefull links ?? Krzytsztof Suwada

Hi All. I need a bit of help extracting the residual error variance from the VarCorr structure from lmer. #Here's a 2-way random effects model lmer.1 <- lmer(rating ~ (1|person)+(1|rater), data = dat) #Get the structure vc.fit <- VarCorr(lmer.1) #results in..... $person 1 x 1 Matrix of class "dpoMatrix" (Intercept) (Intercept) 0.7755392 $rater 1 x 1 Matrix