similar to: Scripting - query

Hi there, I know this is probably a really simple question, but without the correct keywords, or knowledge of the correct function it is hard to search for on the net or within R. How do I increment a dataframe (or similar) name within a loop and assign data? A simple example would be: for(i in 1:10){ test<-i } BUT I want it to be test[i] --- in other words I want my stored data to

Hi, I'm doing anova on a matrix of multivariate data where I want to assess the effect of each column (element). My matrix is 86 rows x 31 columns. I've created a grouping factor of length 86 containing group assignments of 6 types. Then I run: x<- aov(matrix~grouping.factor) summary(aov.fit.raw, test="Wilks") This is working fine enough, but I'm getting different

Hi there, I'm plotting some glass RI values just by plotting plot(x) then I put on my lowess smoother lines(lowess(x)) now I want to put on some 95% Confidence Interval bands of the lowess smoother, but don't know how?? Thanks -- Gareth Campbell PhD Candidate The University of Auckland P +649 815 3670 M +6421 256 3511 E gareth.campbell@esr.cri.nz gcam032@gmail.com [[alternative

Hello, I have a time-series of standards measured for Refractive index. They are daily standards, however, I didn't run one everyday so some days have no data. I can plot the values, but the x-axis does not represent the correct time series (i.e. it's just an evenly spaced 1,2,3 type axis). I want to plot the points with some form of representitive date line on the x-axis. I don't

Hello all, I'm dealing with geochemical analyses of some rocks. If I use the full composition (31 elements or variables), I can get reasonable separation of my 6 sources. Then when I go onto do LDA with the 6 groups, I get excellent separation. I feel like I should be reducing the variables to thos that are providing the most discrimination between the groups as this is important

Hey team, If I have a matrix: 1, 2, 3, 4, 4, 0, 1, 3, 0, 3 2 columns. I want to write an if command that looks at (in this case) row 3 and looks to see if either [3,1] or [3,2] has a zero in it. IF it does have a zero I want the zero to be placed in another matrix in the same position. I know how to do the latter part, I just can't get the if command to look at both cells and deal with

I have some data (REE plots - geochemistry) where I have values 1:14 for the x axis, but have no data for some x values. Here for example, let's say that I don't have data for x=2,5,8. So x<-1:14 y<-c(4, NA, 5, 9, NA, 3.4, 8, NA, 19, 22, 12, 14, 15.3, 15) if I plot the data plot(x,y) and then I want to join with lines lines(x,y) How do I get it so the points join across the

I've made an LDA model on some data from one source. I have some new data that I want to see if I can "place" to the sources in the LDA model. I used the predict function as follows: predict(wak.insitu.ld, wak.alr.alluvial) where wak.insitu.ld is an LDA model generated from some data and wak.alr.alluvial is new data of similar origin. When I look at the results, there is 86

Hi everyone, I have a PCA plot that I'm writing about in the text. There were so many symbols in different colours on it that I didn't include a legend in the plot as it would be useless. So what I was hoping to do was to talk about each set of replicates in the text and when I do that, use their coloured symbol in the text. So what I want to do is to get R to create some high quality

When I run a summary(anova) I get output for all of the elements (columns) as these are multiple - single anova results. Can I store the F values? I can't find the attribute of the fitted model attributes(fit) that stores these F values, and for that matter, P values. Thanks -- Gareth Campbell PhD Candidate The University of Auckland P +649 815 3670 M +6421 256 3511 E

Hello, What I am trying to do is: Generate a density plot of a population of data. This data has a bimodal distribution so I've isolated a couple of possible sub-populations and I want to overlay these two density plots over the first to see whether they are contributing to the bimodal population. I can do this fine with plot(density(...)) and lines(density(...)) . But the resulting plots

Hello, I have a matrix and I want to sample 20 rows that are the the percentiles of 0-100 in 0.05 increments. I have a vector of my sequence (0, 0.05, 0.10, 0.15,....1.0) and also a normalised vector of rownumbers. That is, there are 234 rows (for example) so I do perc<-c(1:234/234) which looks like a bunch of numbers from 0 - 1. In Excel (which I try not to use at every possible

Sorry, the code is incomplete. You get a better result this way... postscript('Circle.eps',paper='special',width=4,height=4) par(mar=c(0,0,0,0)) plot.new() points(0.5,0.5,pch=21,cex=50,bg='gray') dev.off() -----Mensagem original----- De: Rodrigo Aluizio [mailto:r.aluizio em gmail.com] Enviada em: ter?a-feira, 18 de novembro de 2008 19:28 Para: 'Gareth Campbell'

Hello I'm writing an example PCA analysis for some students. I've done PCA on a 2-column matrix to show it at the most simple form (a rotation of two axes). I can't, however, figure out how to plot the rotated axes as lines over top of the original data plotted on the x-y. Does anyone know how to do this? It will be a good way to show how the rotated axes describing the most

Hi all, [this is a bit hard to describe, so if my initial description is confusing, please try running my code below] #WHAT I'M TRYING TO DO I'd appreciate any help in trying to speed up some code. I've written a script that converts a matrix of integers (usually between 1-10,000 - these represent allele names) into two new matrices of normally distributed values (representing

Dear All, The following code extracts from NCBI very nice output for ONE allele of a SNP (often the allele with the second largest frequency - usually termed the minor allele). It gives an average minor allele frequency from all NCBI sources (which is what I want, except I'd like the addition of data for all the other alleles of one SNP) plus a table of minor allele frequencies from each

Hello All, Once again thanks for all of the help to date. I am climbing my R learning curve. I've got a few more questions that I hope I can get some guidance on though. I am not sure whether the etiquette is to break up multiple questions or not but I'll keep them together here for now as it may help put the questions in context despite the fact that the post may get a little long.

Hello R-help community, I have another question about filtering datasets. Please consider the following "toy" data matrix example, called "x" for simplicity. There are 20 different individuals ("ID"), with information about the alleles (A,T, G, C) at six different loci ("Locus1" - "Locus6") for each of these 20 individuals. At any single locus

Hi people, I have made some progress trying to work out how to solve this problem but I have got a bit stuck - sorry if this turns out to be a simple exercise . . Allelic Differentiation (AD) in genetics measures the number of different alleles between (say) two populations eg: Organisms in Pop 1 have alleles: a, b, c, d, e Organisms in Pop 2 have alleles: b, b, c, d, e Different

Dear R user: I am studying the allele data of two populations. the following is the data: a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11 a12 a13 a14 a15 a16 a17 pop1 0.0217 0.0000 0.0109 0.0435 0.0435 0.0000 0.0109 0.0543 0.1739 0.0761 0.1413 0.1522 0.1087 0.0870 0.0435 0.0217 0.0109 pop2 0.0213 0.0213 0.0000 0.0000 0.0000 0.0426 0.1702 0.2128 0.1596 0.1809 0.0957 0.0745 0.0106