similar to: R correlations.

Dear Md Kamruzzaman, I've copied this response to the r-help list, where you originally asked your question. That way, other people can follow the conversation, if they're interested and there will be a record of the solution. Please keep r-help in the loop See below: On 2024-01-17 9:47 p.m., Md. Kamruzzaman wrote: > > Caution: External email. > > > Dear John >

In the "filled bands" part of xYplot of the Hmisc package, is there a way to have multiple bands with multiple lines? or does it just allow one for now? So I had an example bit ago had a made up line and CI, now if I wanted to make a second line with a CI filled in can I put them on the same plot? x<-seq(1,10,1) y<-seq(1,10,1) ci<-y*.10 ciupper<-y+ci

Dear friends i am trying to fit an Ornstein-Uhlenbeck process by MAXIMUM LIKELYHOOD method. i found these formulas on http://www.sitmo.com/article/calibrating-the-ornstein-uhlenbeck-model/ this is the mean-reverting process http://r.789695.n4.nabble.com/file/n4637271/process.txt process.txt and this is the script that i am using....... ouFit.ML=function(spread) { n=length(spread)

Hello, It might be an easy question but if you have many variables to fit in the lm function, how do you take all without specifying var1+var2+...+var2100 in the terms parameter in response ~ terms? Cheers, Carol

Hi all, I want to implement the Xor random canary, so I have to get the return address in the prologue and epilogue of the function. In the prologue of the function, before I insert into the canary on the stack, I can get the return address by: ConstantInt* ci = llvm::ConstantInt::get(Type::getInt32Ty(RI->getContext()), 0); Value* Args1[] = {ci}; CallInst* callInst =

Hi all, I've been trying for hours, but I do not find a Solution. I want to plot 12 variables over time in separate diagrams in one plot/window using lattice. Two columns, six rows. I used print with the split command, but the graphics are getting really small. Can someone please help me. Following data example: dta = data.frame( day=c(1,2,3,4,5,6,7),

Can anyone tell me how I can supply more than one graph to plotCI (gplots) at once? Below is what I tried, also with rbind instead of cbind. What is the way to do this (in general, I think)? Problem is that lines of 1-st and 2-nd series are mixed, while they have nothing to do with each other. I also tried calling plotCI with argument add=TRUE, which didn't seem to work (that is actually

I've a vector of pairwise correlations in the order low-index element precedes the high-index element, say: corr(1,2)=0.1, corr(1,3)=0.2, corr(2,3)=0.3, corr(3,4)=0.4 How can I construct the corresponding correlation matrix? I tried using the "combn"-function in "combinat" package: library(combinat) combn(c(0.1,0.2,0.3,0.4),2) , but to no avail... Thank you for your

I try tu use mob() with my data.frame ('data.frame': 288 obs. of 81 variables; factors, numerics and ordered factors) My response is a binary variable and I should use for modelling a logistic regression (family=binomial). I read in the "MOB" Vignette that I could use a formula like this if I would like to have only partitioning variables apart from the response.

I have survey data that I am working on. I need to make some multi-way tables and regression analyses on the data. After attaching the data, this is the code I use for tables for four variables (sweight is the weight variable): > a <- xtabs(sweight~research.area + gender + a2n2 + age) > tmp <- ftable(a) Is this correct? I don't think I need to use the strata and cluster

Hi, I'm having problems while working with large data sets with R 1.5.1 in windows 2000. Given a integer matrix size of 30 columns and 15000 rows my function should return a boolean matrix size of about 5000 rows and 15000 columns. First of all I tried to run this function on computer with 256 MB of RAM. I increased memory limit of R with memory.limit() up to 512 MB. I was inspecting

Hi all, I have some questions about "DataFlowSanitizer" from "compiler-rt". I want to know how I can test the "DataFlowSanitizer"? Can I configure it to label only some values, i.e, the return values from specific functions? Also, how can I print these labels? Thanks, Dareen -------------- next part -------------- An HTML attachment was scrubbed... URL:

On Mon, Apr 13, 2020 at 1:16 PM Jon Roelofs via llvm-dev < llvm-dev at lists.llvm.org> wrote: > As an update, after lots of fixes from a number of different people > (thanks everyone!), the current list of false-positives on `ninja > check-llvm` for the more stringent Gotcha A diagnostic is: > > LLVM :: Analysis/CostModel/X86/vselect-cost.ll > LLVM ::

Hi Group, Consider a data frame like this: mylabel1 <- rep(c("A","B","C"),each=3) mylabel2 <- rep(c("A","B","C"),3) corrs <- c(1,.8,.7,.8,1,.7,.7,.7,1) myData <- data.frame(mylabel1,mylabel2,corrs) myData mylabel1 mylabel2 corrs 1 A A 1.0 2 A B 0.8 3 A C 0.7 4 B

Hi, I have a list p with different size dataframes and length of over 8000. I'm trying to calculate correlations between the rows of dataframes of this list and columns of another dataset (type data.frame also) so that first column is correlated with all the rows in the list dataframe. Some information from another dataset is also included to the final output (all.corrs). This worked a

Hi people, I want to obtain the adjusted r-square given a set of coefficients (without the intercept), and I don't know if there is a function that does it. Exist???????????????? I know that if you make a linear regression, you enter the dataset and have in "summary" the adjusted r-square. But this is calculated using the coefficients that R obtained,and I want other coefficients

I have the following three models created applying the polymorphic concept ========================================================================== class SoftwareCi < ActiveRecord::Base has_one :ci, :as => :content end class HardwareCi < ActiveRecord::Base has_one :ci, :as => :content end class Ci < ActiveRecord::Base belongs_to :content, :polymorphic => true end The

Why do we get Partial correlation values greater than 1? I have used the default function pcor.mat :-- I have manipulated the default pcor.mat function a bit so ignore tha variables corr_type,element1_in_no,element2_in_no,P.Please ignore the ?pairwise? section and have a look at athe ?listwise ? part i.e else part. *pcor.mat <-

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

Hello, I'm doing some linear regression: >lm<-lm(osas~alp,data) >summary(lm) However, the Rsquared in the output of summary() is not the same as the "standard" Rsquared calculated by spreadsheets, and outlined in statistical guidebooks, being SSR/SSTO. The output says "multiple Rsquared", but it is no multiple regression... What's the difference? Thanks,