similar to: Queue Management

Hello, I am looking into description of surf.ls(spatial) and see under value $beta - the coefficients. When I use polynomial of degree 2 to fit surface I expect to get 4 coefficients: z = a_1 x^2 + a_2 xy + a_3 y^2 + a_4 What do beta really stand for and why do I get $beta vector of length 6? Thakns, Mark

Hi all, I have n independent variables A_1, A_2, A_3,......,A_n, and each with known variances var(A_1), var(A_2),..., but unknown mean. How can I get the approximation of the variance of the product of the variables using numerical computation, i.e. var(A_1*A_2*A_3*.....*A_n)? Thanks. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel: 609-275-2176

When you say that distribution shouldn't be used, do you mean within instcombine rather than some other pass? Or not all as an IR optimization? A dedicated optimization pass that looks for and makes factoring/distribution folds to eliminate instructions seems like it would solve the problems that I'm seeing. Ie, I'm leaning towards the proposal here: https://reviews.llvm.org/D41574

Dear All, I've been searching relevant topics about replacing values, none seemed to be applicable to me... I have a file with many many varieties, and want to replace some of them into different names. I tried various of ways, still don't know how to do that most efficiently.. Here is part of the example data: Gen Rep A_1 1 A_1 2 A_2 1 A_2 2 B_1 1 B_1

Dear R experts, I was wondering if there are any R functions that give the tail area of a sum of chisquare distributions of the type: a_1 X_1 + a_2 X_2 where a_1 and a_2 are constants and X_1 and X_2 are independent chi-square variables with different degrees of freedom. Thanks, Klaus -- "Feel free" - 5 GB Mailbox, 50 FreeSMS/Monat ...

Hi! I want to write portions of my data (3573 columns at a time) to twenty folders I have available titled "A_1" to "A_20" such that the first 3573 columns will go to folder A_1, next 3573 to folder A_2 and so on. This code below ensures that the data is written into all 20 folders, but only the last iteration of the loop (last 3573 columns) is being written into ALL of the

> On May 8, 2018, at 9:50 AM, Daniel Berlin via llvm-dev <llvm-dev at lists.llvm.org> wrote: > > 1. The reassociate pass that exists right now was *originally* (AFAIK) written to enable CSE/GVN to do better. Agreed. The original mindset included a (naive) belief that going with a canonical form was better than teaching redundancy elimination to handle abstractions (as a matter

Hi I have two arbitrarily dimensioned arrays, "a" and "b", with length(dim(a))==length(dim(b)). I want to form a sort of "corner-to-corner" version of abind(), or a multidimensional version of blockdiag(). In the case of matrices, the function is easy to write and if a=matrix(1,3,4) and b=matrix(2,2,2), then adiag(a,b) would return: [,1] [,2] [,3] [,4] [,5]

Hallo everybody, I'm new in r and I"ll appreciate some help! I have a matrix of nrow=30 and ncoll=54,and I would like to generate 50 simulations with tha same size of the matrix!!!That is to say that I want to generate 50 matrices -for my 50 simulations - with the same dimensions! I took my 1st matrix according to the formula that I want to implement: D<-mean_m + U_i*mat_DELTA

Chris, I think some clarifications and examples would be helpful. - LLVM is in SSA. It is in SSA before alias analysis has been >>>> performed. With OA, it has been mentioned that the SSA generation >>>> is >>>> incorrect because it doesn't take alias analysis information into >>>> account. This seems logical, because the definition of

Hello to all, I am having trouble with intregrating a complicated uni-dimensional function of the following form Phi(x-a_1)*Phi(x-a_2)*...*Phi(x-a_{n-1})*phi(x-a_n). Here n is about 5000, Phi is the cumulative distribution function of standard normal, phi is the density function of standard normal, and x ranges over (-infty,infty). My idea is to to use quadrature to handle this integral. But

Dear R-Users, I need to find a smooth function f() and coefficients a_i that give the best fit to y ~ a_0 + a_1*f(x_1) + a_2*f(x_2) Note that it is the same non-linear transformation f() that is applied to both x_1 and x_2. So my first question is how can I do it in R? A more general question is this: suppose I have a utility function U(a_i, f()), where f() is say a spline. Is there a general

On Thu, 6 Nov 2003, Michelle Strout wrote: > Those of us working on the OpenAnalysis project have been looking at > LLVM recently (excellent job on the website BTW). Thanks! I'm just one of the many people who have worked on it though, the praise belongs to them as much as it does to me. :) > This includes researchers at Rice, Argonne, and LLNL. Great! > John Mellor-Crummey

Hello, Apologies if this question has already arised, hope you can help me to the find the solution to this or point the place to look at. I have a multidimensional piece-wise regression linear problem, i.e. to find not only the regression coefficients for each "interval" but also the beginning and ends of the intervals. To simplify it to the one dimensional case and two intervals,

Hello, I'm very new to using R, but I was told it could do what I want. I'm not sure how best to enter the information but here goes... I'm trying to transfer the following integral into R to solve for ln(gamma_1), on the left, for multiple instances of gamma_i and variable N_i. gamma_i is, for example, (0, 0.03012048, 0.05000000, 0.19200000, 0.44000000, 0.62566845) N_i (N_1 or

> I asked myself the same question. Without mod, how do you ensure that for instance the expression 2*i+255 was not actually 2*i-1 ? I think it is not possible in general, but I believe it is possible in case of affine expressions used as GEP indices. I assume, GEP indices (except indexing into struct) are interpreted as signed integers. It isn't explicitly stated in the LangRef, but

Hello! I would like to use constrain to sum coeficients of a factor to 0 instead of classical corner contraint i.e. I would like to fit a model like lm(y ~ 1 + effectA + effectB) and say get parameters intercept effectA_1 effectA_2 effectB_1 effectB_2 effectB_3 where effectA_1 represents deviation of level A_1 from intercept and sum(effectA_1, effectA_2) = 0 and the same for factor B. Is

Dear useRs, I am trying to model a time series with a transfer function. I think it can be put into the ARMA framework, and estimated with the 'arima' function (and others have made similar comments on this list). I have tried to do that, but the results have so far been disappointing. Maybe I am trying to make 'arima' do something it can't... The data are time series of

As I have previously asked, in response to a similar question: Is this a homework problem? cheers, Rolf Turner rolf at math.unb.ca

Hi R-helpers, I'm new to time series modelling, but my requirement seems to fall just outside the capabilities of the arima function in R. I'd like to fit an ARMA model where the variance of the disturbances is a function of some exogenous variable. So something like: Y_t = a_0 + a_1 * Y_(t-1) +...+ a_p * Y_(t-p) + b_1 * e_(t-1) +...+ b_q * e_(t-q) + e_t, where e_t ~ N(0, sigma^2_t),