similar to: Read the data from a text file and reshape the data

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has

I have the following binary data set: Sex Response 0 1 0 159 162 1 4 37 My commands library(MASS) sib.glm=glm(sib~sex,family=binomial,data=sib.data) summary(sib.glm) The coefficients in the output are Estimate Std. Error z value Pr(>|z|) (Intercept) -3.6826 0.5062 -7.274 3.48e-13

Dear List, My data consist of nine columns and about 50,000 rows. It looks like this. -9.0225 3.46464 2.80926 -0.3847 3.73735 1.1058 -2.98936 1.38901 -8.1846 -2.4315 -5.1189 1.8225 3.3798 1.7874 4.693 -3.9286 1.4266 5.7849 -3.4894 -4.0305 3.7879 3.5195 2.9186 2.8685 -6.126 4.978 4.9381 4.5282 3.62558 -3.0455 4.6518 1.39746 0.68652 3.5708 -3.6404 -4.2963 -1.3183 0.6752 -4.0382 -2.5386

I have two large files (2+MB), one of which is a corrupted version of the other. I tried to rsync the good file to the corrupted one, hoping it would repair the few bad bytes, but it did nothing. (I tried to be careful not to specify the --archive or --update flags, either explicitly or implicitly.) The original problem occurrend on a transfer from one computer to another. I then did a number

Hello R-help   I am working with large data table that have the occasional label,  a particular time point in an experiment. E.g: "Time (min)", "R1 R1", "R2 R1", "R3 R1", "R4 R1" .909, 1.117, 1.225, 1.048, 1.258 3.942, 1.113, 1.230, 1.049, 1.262 3.976, 1.105, 1.226, 1.051, 1.259 4.009, 1.114, 1.231, 1.053, 1.259 4.042, 1.107, 1.230, 1.048, 1.262

Hi All, I was wondering if someone could help me to solve this issue with lmer. In order to understand the best mixed effects model to fit my data, I compared the following options according to the procedures specified in many papers (i.e. Baayen <http://www.google.it/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CDsQFjAA

Hi I have a follow up question, relating to subsetting to list items. After using the list and min(sapply()) method to adjust the length of the variables, I specify a dynamic regression equation using the variables in the list. My list looks like this: Dcr<- list(Dcre1=DCred1,Dcre2=DCred2,Dcre3=DCred3,Dbobc1=DBoBC1,Dbobc2=DBoBC2,Dbobc3=DBoBC3,...) By specifying the list items with names, I

Consider the following example (based on an example in Pat Altham's GLM notes) pyears <- scan() 18793 52407 10673 43248 5710 28612 2585 12663 1462 5317 deaths <- scan() 2 32 12 104 28 206 28 186 31 102 Smoke <- gl(2,1,10,labels=c("No","Yes")) Age <- gl(5,2,10,labels=c("35-44","45-54","55-64","65-74","75-84"),

Dear All: In the attached file, I have 3 group patients, and there are 5 in each group (the groups are decided by the prefix of the idno). I want draw a repeat measurement comparison figure. My goal is to list 5 patients from same group on one horizontal line. But xyplot sounds pick them randomly (or I was confused?). Could you please help me modify the following code to accomplish this?

I have fitted the faults.data to glm.nb and to the function negbin from the package aod. The output of both is the following: summary(glm.nb(n~ll, data=faults)) Call: glm.nb(formula = n ~ ll, data = faults, init.theta = 8.667407437, link = log) Deviance Residuals: Min 1Q Median 3Q Max -2.0470 -0.7815 -0.1723 0.4275 2.0896 Coefficients:

sort() and order() are not quite the same, as "one knows": o order allows breaking ties by more than one argument; o sort allows a 'partial' and 'na.last' argument Still, the following timing (on a `simple' UltraSparc I) suggest that actually two different algorithms are used > N <- 10000 > typeof(x0 <- 1:N) # --- x0 : already sorted --- [1]

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

Dear all, Does any one knows why should I get the following error message, when trying to do a simple data.frame?? DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS p,DSSp,Slope, CanDens,NearestSp) Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, : arguments imply differing number of rows: 202, 0 The data I am using

Dear R list, I've been attempting to interpret the results from a three-way ANOVA. I think I understand contrasts and the R defaults for these (treatment contrasts). My question is: what is the intercept in this test? As far as I can tell, its NOT the expected value of a point that belongs to the first level of all three explanatory factors (because there is only one point that satisfies these

Hi, I need an old version of wine, particulary wine20021219. I can see the source at source.winehq.org , but I can't download it there. (OK, theoretically I can, but I won't open all files one by one and copy the contents to a text file ;) ) How/Where can I download wine20021219? Regards, Victor

R Help - I'm trying to run a correlation matrix with a covariate of "age" and will at some point will also want to covary other variables concurrently. I'm using the "psych" package and have tried other methods such as writing a loop to extract semi-partial correlations, but it does not seem to be working. How can I accomplish this? library(psych) > set.cor(y =

Does R graphics have a way to easily label the horizontal axis by the reciprocal of the scaled value? -- View this message in context: http://r.789695.n4.nabble.com/Graphics-Reciprocal-labeling-tp3949054p3949054.html Sent from the R help mailing list archive at Nabble.com.

Hi All, I have a vector of data, a vector of bin breakpoints and I want to put my data in the bins and then extract fanciful informations like the mean value of each bin. I know I can write my own function, but I would have thought that R should have somewhere a function that took as arguments something like (data, breaks, what to do with the data in the bins). I surey could not find it

Dear Thierry, thank you for the quick reply. I have only one question about the approach you proposed. As you suggested, imagine that the model we end up after the model selection procedure is: mod2.1 <- lmer(dT_purs ~ T + Z + (1 +T+Z| subject), data =x, REML= FALSE) According to the common procedures specified in many manuals and recent papers, if I want to compute the p_values relative to

My internal lan is small, 100mb, all wired. aastra phones. sip show peers ....... 142/... 10.10.10.42 D A 5060 OK (136 ms) 144/... 10.10.10.44 D A 5060 OK (138 ms) 145/... 10.10.10.45 D A 5060 OK (133 ms) But pings are < 1ms: ping 10.10.10.42 ........ rtt min/avg/max/mdev = 0.479/0.483/0.497/0.021 ms Why are the sip latencies so