similar to: aov design questions

Dear Sir or Madam, I am a student at MSc Probability and Finance at Paris 6 University/ Ecole Polytechnique. I am using R and I can't find an answer to the following question. I will be very thankful if you can answer it. I have two vectors rendements_CAC40 and rendements_AlcatelLucent. I use the lm function as follows, and then the sumarry function: regression=lm(rendements_CAC40 ~

Dear R users I have run an regression and want to extract the p value of the F statistics, but I can find a way to do that. x<-summary(lm(log(RV2)~log(IV.m),data=b)) Call: lm(formula = log(RV2) ~ log(IV.m), data = b[[11]]) Residuals: Min 1Q Median 3Q Max -0.26511 -0.09718 -0.01326 0.11095 0.29777 Coefficients: Estimate Std. Error t value Pr(>|t|)

Dear R devel, Apologies for these (most probably trivial) questions, doing my first attempt to call C from R (and actually learning C in the process). I need to pass a matrix to C, and after reading R-exts.pdf (many times), I was unable to find how to handle matrices at C-level... except for, what probably is the answer, that matrices are in fact vectors with dimensions. This is a sample code I

Hello, I have a C++ code for 2D random walks with traps and I want to convert it in a R code with its syntaxs, can anyone help??????? It's easy for me to adapt the body but I want help with the beginig (variable declaration) and th end exporting the output to a file ( like write.table() or sink() ) Thank you... #include <iostream> #include <math.h>#include

Dear list, I just tried to do the same thing, and did not find anything on a weighted qqplot. My weights are actually counts (positive integers). Here is a modification of qqplot, following Duncan Murdoch's suggestion. Any feedback would be welcome! Thanks, Jean-Christophe weighted.qqplot <- function (x, y, plot.it = TRUE, xlab = deparse(substitute(x)), ylab = deparse(substitute(y)),

Dear all, I am trying to learn lapply. I would like, as a test case, to try the lapply alternative for the Shadowlist<-array(data=NA,dim=c(dimx,dimy,dimmaps)) for (i in c(1:dimx)){ Shadowlist[,,i]<-i } ---so I wrote the following--- returni <-function(i,ShadowMatrix) {ShadowMatrix<-i} lapply(seq(1:dimx),Shadowlist[,,seq(1:dimx)],returni) So far I do not get same results

Hello everyone, I am using ggplot to plot but I am getting the following error which I do not understand Error: geom_text requires the following missing aesthetics: label My code is dimx<-256 library(ggplot2) dev.new() xandy<-expand.grid(seq(1:dimx),seq(1:dimy)) xx<-data.frame(xandy[[1]],xandy[[2]],Powermap=Powermap) subsetxx<-subset(xx, xx$Powermap>threshold)

Dear all, I am attempting to convert 10 NetCDF files into a single NetCDF file, due to the data input requirements of a model I hope to use. I am using the ncdf package, version 1.6. The data are global-scale water values, on a monthly basis for 10 years (ie. 120 months of data in total; at present the data are separated by year, with 12 months of data in each file - mrunoff_1986 through to

Dear all, I am attempting to convert 10 NetCDF files into a single NetCDF file, due to the data input requirements of a model I hope to use. I am using the ncdf package, version 1.6. The data are global-scale water values, on a monthly basis for 10 years (ie. 120 months of data in total; at present the data are separated by year, with 12 months of data in each file - mrunoff_1986 through to

Hi, I have a list called ds which has the following attributes: attributes(ds) $names [1] "adj.r.squared" "fstatistic" "intercept" "slope" [5] "std.error" "tstatistic" I want to replace all the NaN is ds with 0, and after searching past posts I found I can hardcode it like this:

hello, how can take the string in the data frame. right now i have a table that create as a data frame and stored in the file called "data.xls" and now i want to read data frame as a table in my another r program, i used the following command: the first column of the data frame is just one number called "num", but the second one a list of string, called "name". d

Hi, While exploring how summary.lm generated its output I came across a section that left me puzzled. at around line 57 R <- chol2inv(Qr$qr[p1, p1, drop = FALSE]) se <- sqrt(diag(R) * resvar) I'm hoping somebody could explain the logic of these to steps or alternatively point me in the direction of a text that will explain these steps. In particular I'm puzzled

Dear All, Sorry to bother I want to write a function in R using if Say I have a dataset x, if x[i]<0, then x[i]=x[i], if x[i]>0, then x[i]=0 for example, x=-3:3, then using the function, x becomes [-3,-2,-1,0,0,0,0] I write the codes as follows, gjr=function(x) {lena=length(x) for(i in 1:lenx) if (x[i]<0) return (x[i]) if (x[i]>0) return (0) x} but then, doing gjr(x? it only

could someone explain why the name of FPVAL gets " .value" concatenated onto it when the code below is run and temp is returned. I've been trying to figure this out for too long. It doesn't matter when I put the FPVAL in the return statement. It happens regardless of whether it's first or last. Thanks. f.lmmultenhanced <- function(response, pred1, pred2) {

Hi, perhaps this is a stupid question, but i need some help about Helmert contrasts in the Cox model. I have a survival data frame with an unordered factor `group' with levels 0 ... 5. Calculating the Cox model with Helmert contrasts, i expected that the first coefficient would be the same as if i had used treatment contrasts, but this is not true. I this a error in reasoning, or is it

I'm wondering which textbook discussed the various contrast matrices mentioned in the help page of 'contr.helmert'. Could somebody let me know? BTW, in R version 2.9.1, there is a typo on the help page of 'contr.helmert' ('cont.helmert' should be 'contr.helmert').

inputfille snpid indid genotype gvariable probeid gene geneexpression rs1040480 CHB_NA18524 C/T 2 GI_19743926-I PTPRT 5.850586 rs1040480 CHB_NA18526 C/C 1 GI_19743926-I PTPRT 6.028641 rs1040480 CHB_NA18529 C/C 3 GI_19743926-I PTPRT 5.944392 rs1040481 CHB_NA18532 C/C 1 GI_19743926-I PTPRT 5.938578 rs1040481 CHB_NA18537 C/C 2 GI_19743926-I PTPRT 5.874439 rs1040481 CHB_NA18540 C/C 3 GI_19743926-I

Hi Folks, I've encountered something I hadn't been consciously aware of previously, and I'm wondering what the explanation might be. In (on another list) using R to demonstrate the difference between different contrasts in 'lm' I set up an example where Y is sampled from three different normal distributions according to the levels ("A","B","C")

Hello all, thanks for your time and help. Below are my commands, and it generates a really nice plot, however I am not happy with the reorder() function. I would like the order to be the same as they appear in the genotype variable "genotype <- c("CJ1450 NW 4/25/12","CJ1450 BAL 4/25/12","CJ1450 NW 4/27/12","CJ1450 BAL 4/27/12","CJ1721 NW

For every specific V1 and V4 pair (ex:A and P) calculate Linear regression of V3(y-axis) and V2(x-axis) and print p value along with the pair (output). INPUT ############# V1 V2 V3 V4 A 1 2.5 P A 2 2.8 P A 3 3.2 P A 2 1.1 Q A 3 1.7 Q A 1 2.2 Q B 1 2.5 P B 2 2.9 P B 3 3.0 P SCRIPT ####### data1<-read.table("INPUT", header=TRUE) fm <- lmList(V3~V2|V1,V4 data=data1) get.pval <-