similar to: Automatic routine - NEW

Hi, I would like to write a little automatic routine in R, but i am a too much of a beginner for that. I will appreciate any help regarding this particular problem. Let?s suppose I have a data.frame with j columns (from 1 to n) and i rows (from 1 to p). I would like to write a procedure which reads every column j (j from 1 to n) and compare each value with the interval [0,1]. If z(i,j) is

Hello again, There is any package which does Z aware (real 3D) interpolations? It can be any method (IDW, kriging or spline) but it should take into consideration not only x and y coordinates for interpolation, but also z coordinate. I looked into different packages but it seems i didn't find the right one. The ultimate goal is to import the output into a GIS (Geographical Information

Hi, I am a beginner user of R. I have a trivial question ? I am almost ashamed I cannot figure it out does not matter how many times I am reading the help. I have a table in .txt format, tab delimited. I can read it with ?read.delim()? with no problems. Afterwards I would like to use boxplot function to see if there are any outliers in the column 5 of my data called TPAH16.ppm In the

Hi, I am trying to increase the memory R can use. I am running R under Windows on a machine with 2 GB of physical RAM and 4GB of paged memory. I wrote in the R property windows --sdi --max-mem-size=4094M, but the R itself when it is doing a bayesian modelling (geoR) it stops at 1,096K and i get memory errors because it cannot allocate a new segment of about 500K of memory. I don't have

Hi, Thank you so much for all your rapid answers. I am impressed. What i didn't know was that i have to assign my data to an object to work further on. It was not clear from the help (at least for me) that 'data()' itself is calling data already in R packages. All of you make that clear. Now, if you can suggest any good package to use for identifying outliers it will be great

Hi everybody, I would like to plot only a part of a data frame, and identify the IDs for all the points with values higher than a certain value. I will try to be more explicit: I did a qqnorm plot of my data. It is obvious from the plot that all the sample quantiles which are in Theoretical Quantiles = or > than 1 belong to another group. To be sure about that I plot the cooks.distance

Hi, Very so often when i am plotting something, doing a histogram, or whatever i am struggling to find out which are the numbers for different colors, palette names, types of lines, symbols, etc. Is there any documentation on line with all these numbers / names and the associated symbol / color??? For example if i am using the command image it uses a palette from red to yellow, with red the

hi y'all, I am wondering if there is any special command, function, package, etc to help me doing a cumulative distribution function, with y-scale - probability scale. I tried the help in R and i got the following answers: cumsum(base) Cumulative Sums, Products, and Extremes ecdf(stepfun) Empirical Cumulative Distribution Function cpgram(ts) Plot

Hi, First of all - thank you for the answers regarding shared library. If i am attempting to translate the library from Linux to Windows - i think i will need some heavy baby-sitting ;-))) It is way out of my league - for now. Meanwhile i have this new question: suppose i have a data.frame with x and y columns and 10 rows, 1 to 10. I also have a variable m (or an array if you like) with 5

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

Hi y'all, First of all many thanks to Christian, Petr and Spencer for their replies. Your answers helped me to learn few more triks since then ;-) Now i have a question relating "aov". When i use aov i end up with 4 plots. How do i "see" the data behind those plots? I know about summary - but this gives me only some statistical info. Also, if i want to identify which

Hello, I have a data-set containing 22 variables, after appropriate transformations etc I ran a kmeans cluster analysis for 4 clusters , I ran it 20 times to find a result with the lowest within sum of squares. My question is how best do I go about finding out what the characteristics are of each cluster? Is one cluster dominated by a particular set of variables or by a particular

Hi everybody, I am using quite frequently the "robust" package and until now i never had any problems. Actually last time i used it was last Friday very successfully. Anyway, today anytime i want to use the function "fit.models" i get the following error even if i use the example form the help file: data(woodmod.dat) woodmod.fm <- fit.models(list(Robust =

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Hello, I'm new in R and I want to do one thing that is very easy in excel, however, I cant do it in R. Suppose we have the data frame: data<- data.frame(A=c("a1","a2","a3","a4","a5")) I need to obtain another column in the same data frame (lets say B=c(b1,b2,b3,b4,b5) in the following way: b1=a1/(a1+a2+a3+a4+a5)

Hi, I am doing a barplot, and the fist bar is very big (high values) and the rest of the bars are quite small (small values). So - is there any way to make the Y scale logarithmic so that i have a wider distance from 0 to 50 for example than for 50 to 100, and so on? Thanks in advance for any help, Monica

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I would like to compare two data sets saved as text files (example below) to determine if both sets are identical(or if dat2 is missing information that is included in dat1) and if they are not identical list what information is different between the two sets(ie output "a1", "a3" as the differing information). The overall purpose would be to remove "a1" and

Dear All, Here is a hypothetical sample (sorry for the clumsy code): A1 <- matrix(1:5, nrow=5, ncol=1) A2 <- matrix(6:10, nrow=5, ncol=1) A3 <- matrix(11:15, nrow=5, ncol=1) A4 <- matrix(16:20, nrow=5, ncol=1) A5 <- matrix(21:25, nrow=5, ncol=1) A6 <- matrix(26:30, nrow=5, ncol=1) B1 <- matrix(c(A1, A2, A3), nrow=5, ncol=3) B2 <- matrix(c(A2, A3, A4), nrow=5, ncol=3) B3

I have a dataset that is basically structureless. Its dimension varies from row to row and sep(s) are a mixture of tab and semi colon (;) and example is HEADER1 HEADER2 HEADER3 HEADER3 A1 B1 C1 X11;X12;X13 A2 B2 C2 X21;X22;X23;X24;X25 A3 B3 C3 A4 B4 C4 X41;X42;X43 A5 B5 C5 X51 etc., say. Note that a blank