similar to: ordering a vector

Dear R listers, I have a data file looks like the following: Testing marker: s_1 --------------------------------------------- Allele df(0) -LnLk(0) df(T) -LnLk(T) ChiSq p 3 7995 29320.30 7994 29311.85 16.90 4e-05 (2229/8000 probands) Testing marker: s_2 --------------------------------------------- Allele df(0)

On 04/11/2017 10:20 PM, Daniel Nordlund wrote: > Tirthankar, > > "random number generators" do not produce random numbers. Any given > generator produces a fixed sequence of numbers that appear to meet > various tests of randomness. By picking a seed you enter that sequence > in a particular place and subsequent numbers in the sequence appear to > be unrelated.

Dear List, Recently I got the comment that the implementation of the random number generator used by default in R (Mersenne-Twister) could not be "safe" for 64-bits machines, so I decided to put the question here because I do not have expertise in that topic, and because this question could be "too technical for R-help's audience". I apologise if this is not the case.

Hi, my data frame consist of 8 Variables and 120 000 observations. With those datas I am running a PCA and after I want to calculate the Volume of the PCA-cloud of certain subsets of my data. Does anyone have an idea about a function that can do this? Thanks [[alternative HTML version deleted]]

I thought this would be trivial, but I can't find a package or function that does this. I'm hoping someone can guide me to one. Imagine a simple case with two survival curves (e.g. treatment & control). I just want to calculate the difference in KM estimates at a specific time point (e.g. 1 year) plus the estimate's 95% CI. The former is straightforward, but the estimates not

Hi, I am trying to make a sequence and am using a for loop for this. I want to start off with an initial value ie S[0]=0 then use the loop to create other values. This is what I have so far but I just keep getting error messages. #To calculate the culmulative sums: s<-rep(0,207) #as this is the length of the vector I know I will have s<-as.vector(s)

Hi all, I want to do plot() in a loop to make 10 graphs, so I have some code like for (i in 1:10) { plot(... ... , xlab = expression(g[i]) ) } I expect g_1, g_2, and so on appear on x labels, but it simply prints g_i for each graph. Does anybody know how to get around this problem? Thanks. NL

Hello everybody. I have this object procedure property sensor_data sensor_date 1 S_10 nord 626821.0 2002-09-30T00:00:00+0200 2 S_10 nord 626821.0 2002-12-05T00:00:00+0100 3 S_10 nord 626821.1 2008-07-31T00:00:00+0200 4 S_1000 nord 626496.8 2002-09-30T00:00:00+0200 5 S_1000 nord 626496.8 2002-12-05T00:00:00+0100 6 S_1000

Hi Everybody, please can you help me how to call BayesX in R in order to see the graph already exist in BayesX Thanks ---------- Forwarded message ---------- From: <r-help-request@r-project.org> Date: Sat, Jan 22, 2011 at 5:00 AM Subject: R-help Digest, Vol 95, Issue 22 To: r-help@r-project.org Send R-help mailing list submissions to r-help@r-project.org To subscribe or

Hi All, I have a 1000x1000000 matrix. The calculation I would like to do is actually very simple: for each row, calculate the frequency of a given pattern. For example, a toy dataset is as follows. Col1 Col2 Col3 Col4 01 02 02 00 => Freq of ?02? is 0.5 02 02 02 01 => Freq of ?02? is 0.75 00 02 01 01 ? My code is quite simple as the following to find the pattern ?02?.

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

Hi everyone, I am trying to compare proportions among groups using the logistic regression approach as follows: 1) Fit the model log(p_i/(1-p_i)) = M + G_i, where p_i is the probability of success in group i and G_i is the effect of group i, i=1,..,I. 2) Test the hypotheses: Ho: G_1 = G_2 = ... = G_I (the probability of success is the same for all groups) versus Ha: at least two

Here is a programming question. The code I am using is quite slow and I was wondering if there is a way to get rid of the for loop. I am dealing with "interaction" in 2x2 table, and am using Edwards's G_I (Likelihood, p. 194). I label the cells in the table as follows stim response "y" "n" total -------------------------------- y hit miss nsignal

> On 5 Nov 2017, at 15:17 , Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > > On 04/11/2017 10:20 PM, Daniel Nordlund wrote: >> Tirthankar, >> "random number generators" do not produce random numbers. Any given >> generator produces a fixed sequence of numbers that appear to meet >> various tests of randomness. By picking a seed you enter

> On Jun 24, 2019, at 10:53 AM, Tian, Xinmin <xinmin.tian at intel.com> wrote: > > To me, it is also an issue related to SIMD signature matching when the vectorizer kicks in. Losing info from FE to BE is not good in general. > Yes, we cannot loose such information. In particular, the three examples I reported are all generating i64 in the scalar function signature: // Type 1

For example, Type 2 case, scalar-foo used call by value while vector-foo used call by ref. The question Johannes is asking is whether we can decipher that after the fact, only by looking at the two function signatures, or need some more info (what kind, what's minimal)? I think we need to list up cases of interest, and for each vector ABI of interest, we need to work on the requirements and

On 12 December 2016 at 16:49, Francesco Petrogalli <Francesco.Petrogalli at arm.com> wrote: > I am not sure I understand here. In my patch, all I am doing is “vector > symbol awareness generation”. There are no globals that are generated in > the final object file, it is just the TargetLibraryInfoImpl that is being > populated with the info needed by the vectorizer. The

> What is a `"logically"-widened alwaysinline wrapper for the vector function`? Can you provide an example? Also, what is the `tricky processing` you are referring to that the vectorizer should care about? For the case mentioned earlier: float MyAdd(float* a, int b) { return *a + b; } __declspec(vector_variant(implements(MyAdd(float *a, int b)),

Hi, I am having trouble using constrOptim. My target is to do a portfolio optimization and there some constraints have to be fulfilled. 1) The weight of each share of the portfolio has to be greater than 0 2) The sum of these weights has to be 1 I am able to fulfill either the first or the second constraint but not both. One simple way would be to fulfill the first constraint by using optim as

Dear R-Helpers, I have a matrix where the first column is known. The second column is the result of multiplying this first column with a constant "const". The third column is the result of multiplying the second column with "const"..... So far, I did it like this (as a simplified example): nr.of.columns <- 4 myconstant <- 27.5 mymatrix <- matrix(numeric(0), nrow=5,