similar to: Variable Selection for data reduction and discriminant anlaysis

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

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

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 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

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 have a vector: alleles.present<-c("D3", "D16", ... ) The alleles present changes given the case I'm dealing with - i.e. either all of the alleles I use for my calculations are present, or some of them. Depending on what alleles are present, I need to make matrices and do calculations on those alleles present and completely disregard any formula or other use of 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

Warranty on Accuracy, Precision, Legality, ... of R in Research (These questions may well have been raised.) What is the implied warranty of using R for research & publications, consulting, etc.? Alternately, how does one obtain such a warranty? Your answers will be much appreciated. Perhaps you can point me to some websites which discussed this subject in the past. Thanks & regards

>>>>> Rich Shepard >>>>> on Mon, 22 Jan 2024 07:45:31 -0800 (PST) writes: > A statistical question, not specific to R. I'm asking for > a pointer for a source of definitive descriptions of what > types of data are best summarized by the arithmetic, > geometric, and harmonic means. In spite of off-topic: I think it is a good

On Mon, 22 Jan 2024, Martin Maechler wrote: > I think it is a good question, not really only about geo-chemistry, but > about statistics in applied sciences (and engineering for that matter). > John W Tukey (and several other of the grands of the time) had the log > transform among the "First aid transformations": > > If the data for a continuous variable must all be

Ah.... LOD's, typically LLOD's ("lower limits of detection"). Disclaimer: I am *NOT* in any sense an expert on such matters. What follows are just some comments based on my personal experience. Please filter accordingly. Also, while I kept it on list as Martin suggested it might be useful to do so, most folks probably can safely ignore the rant that follows as off topic and not

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'

A statistical question, not specific to R. I'm asking for a pointer for a source of definitive descriptions of what types of data are best summarized by the arithmetic, geometric, and harmonic means. As an aquatic ecologist I see regulators apply the geometric mean to geochemical concentrations rather than using the arithmetic mean. I want to know whether the geometric mean of a set of

I'm in e-mail contact with a geochemist who maintains a well regarded geochemistry web site. He's drawing diagrams either with a Turbo Pascal program running in a DOS window or with Excel. I'm trying to persuade him that R would be a better choice. Something he's particularly keen on is ternary diagrams. I think he is talking about ternary phase diagrams, and if so, it looks as

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