similar to: ANOVA tables - storing F values

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

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

Hi, When I run the survfit function, I want to get the restricted mean value and the standard error also. I found out using the "print" function to do so, as shown below, print(km.fit,print.rmean=TRUE) Call: survfit(formula = Surv(diff, status) ~ 1, type = "kaplan-meier") records n.max n.start events *rmean *se(rmean) median 200.000

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

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

Dear all, I am confused with the behaviour of survfit with newdata option. I am using the latest version R-2-15-0. In the simple example below I am building a coxph model on 90 patients and trying to predict 10 patients. Unfortunately the survival curve at the end is for 90 patients. Could somebody please from the survival package confirm that this behaviour is as expected or not - because I

Hi, I'm going crazy trying to plot a quite simple graph. i need to plot estimated hazard rate from a cox model. supposing the model i like this: coxPhMod=coxph(Surv(TIME, EV) ~ AGE+A+B+strata(C) data=data) with 4 level for C. how can i obtain a graph with 4 estimated (better smoothed) hazard curve (base-line hazard + 3 proportional) to highlight the effect of C. thanks!! laudan [[alternative

Hi, I want to fit multiple cox models using the coxph() function. To do this, I use a for-loop and save the relevant results in a separate matrix. In the example below, only two models are fitted (my actual matrix has many more columns), one gives a warning message, while the other does not. Right now, I see all the warning message(s) after the for-loop is completed but have no idea which model

Hi everybody, I am currently trying to forecast some double seasonal time series by using the function dshw. I want to access the standard errors to build the confident interval for my forecast. I am using to following code : fit<-dshw(eem,period1=7,period2=48,h=48) then by using summary(fit), I see that my se are contained in the vector : $s20 but when I call fit$s20, I get NULL. I

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 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

Using R 2.10 on Windows: I have a filtered database of 650k event observations in a data frame with 20+ variables. I'd like to be able to quickly generate estimate and plot survival curves. However the survfit and cph() functions are extremely slow. As an example: I tried results.cox<-coxph(Surv(duration, success) ~ start_time + factor1+ factor2+ variable3, data=filteredData) #(took a

Hi everyone. There's been several threads on baseline hazard in Cox model but I think they were all on cumulative baseline hazard, for instance http://tolstoy.newcastle.edu.au/R/help/01a/0464.html http://tolstoy.newcastle.edu.au/R/help/01a/0436.html "basehaz" in package survival seems to do a cumulative hazard. extract from the basehaz function: sfit <- survfit(fit) H