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...acing 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 2 B_3 1 B_3 2 OP1_1 1 OP1_1 2 OP1_5 1 OP1_5 2 For example, I want to replace A_1, B_3, OP1_1 into different name "Wynda" So that the expected file should become: Gen Rep Wynda 1 Wynda 2 A_2 1 A...

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 an...

...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 N_2) is between 0 and 1 so that N_1+N_2=1, so if N_1=(0,.166,.180,.250,.325,.374), then N_2=(1.000, 0.834, 0.820, 0.750, 0.675, 0.626) a_i (a_1 or a_2) So, for gamma_i (in this case gamma_2), N_i (N_2), and a_i (a_2) first the following a_i = ln(gamma_i)/(1-N_i)^2 then, ln(gamma_1) = -a_2*N_1*N*2 - integration (from N_1=1, to N_1) a_2 dN_1 I hope that makes sense...

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 ...

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

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 optimizer that could find...

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 since Phi has not cloaed form, I do...

...will be good to bear it in mind. HOWEVER, I don't see we have any feasible solution without namespaces, since whichever version is loaded last wins in the usual scoping rules. If B requires A version 1 and C requires A version 2 and they are loaded in that order the search path will be C A_2 B A_1 (using Depends) or A_2 C A_1 B (using require) and code in B will find objects from A_2 if they are in there. Without versioned namespace imports I don't see how this helps: am I missing something? (In R<=2.0.0 if you have a namespace in A you can't import from it, at least in a...

...0 0 [2,] 1 1 1 1 0 0 [3,] 1 1 1 1 0 0 [4,] 0 0 0 0 2 2 [5,] 0 0 0 0 2 2 I am trying to generalize this to two higher dimensional arrays. If x <- adiag(a,b) then I want all(dim(x)==dim(a)+dim(b)); and if dim(a)=c(a_1, a_2,...a_d) then x[1:a_1,1:a_2,...,1:a_d]=a, and x[(a_1+1):(a_1+b_1),...,(a_d+1):(a_d+b_d)]=b. Other elements of x are zero. The fact that I'm having difficulty expressing this succinctly makes me think I'm missing something basic. If a and b have identical dimensions [ie all(dim(a)==dim(b))...

...0, 0.318, 0.124, 0.096, 0, 0, 0, 0.012, 0, 0, 0.002, 0, 0, 0, 0.053, 0.178, 0.068, 0.126, 0, 0.001, 0.001, 0, 0.001, 0, 0, 0) matplot(cbind(flow,rain), type="lh") # Note that 'u' is highly skewed. # The system can be modelled by this transfer function: # x[i] <- a_1*x[i-1] + a_2*x[i-2] + b_0*u[i] + b_1*u[i-1] # I happen to know that a good model is a_1 <- 1.6545 a_2 <- -0.6580 b_0 <- 0.1149 b_1 <- -0.1115 # (This was estimated by a proprietary program using # "Simple Refined Instrumental Variable" algorithm). # The transfer function differs from th...

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

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...nt on this scenario. Agent** can also shuffling one campaign to anther campaign. * Now i want to do some work with queue.I want to use single queue to managing this. Eg: campaign Agent Login A a_1,a_3 (In campaign A 2 agents are login) B a_2,a_1 (In campaign B 2 agents are login) C a_3,a_1,a_4 (In campaign C 3 agents are login) D a_4,a_5,a_3 (In campaign D 3 agents are login) E a_1,a_3,1_2...

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

...n 1:length(vec_IS)){ for (j in 1:length(vec_IT)){ Yr_m<-rnorm(54,m=0,sd=1) mat_Yr_m[,j]<-Yr_m delta_i<-lower_m%*%mat_Yr_m[,j] mat_delta[,j]<-as.vector(delta_i) } DELTA_1<-mat_delta[,1] DELTA_2<-mat_delta[,2]-a_1*mat_delta[,1] for (t in 3:length(vec_IT)){ mat_DELTA[,t]<-mat_delta[,t] - a_1*mat_delta[,t-1] - a_2*mat_delta[,t-2] } mat_DELTA[,1]<-DELTA_1 mat_DELTA[,2]<-DELTA_2...

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 folders (A_1 to A_20) rather than the...

...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 the code seems to treat them this way. Am I correct? If the result of an affine expression: a_1*i_1 + a_2*i_2 + ... + a_n*i_n is interpreted as signed value during the program run, it should be safe to assume during the program analysis that all operations (coefficients) are signed - signed evaluation of such an expression will bring the same result as evaluation of the expression using original sig...

> 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

>However, there is one issue I have ignored - possibility of overflow in >the index expression. Suppose, we have such a loop: > for (i8 i = 0; i != 200; ++i) { > A[2 * i + 5] = ... > ... = A[2 * i + 3] > } >If both index expressions are evaluated in 8-bit arithmetic, >then the dependence equation should be solved in modular arithmetic: > 2 * i + 5 == 2 * (i +

...re (unfortunately the search function at http://www.ruby-forum.com/forum/10 is disabled at the moment). If yes, then a pointer to a solution would be great. I want to create a sortable tree with scriptaculous Sortable. There are several categories and subcatgories: cat_a - --subcat_a_1 - --subcat_a_2 cat_b - --subcat_b_1 cat_c cat_d - --subcat_d_1 and so on, you get the point. Now I want to sort subcategories inside a category and move them from e.g. cat_a to cat_d and I also want to sort the main category order itself (e.g. moving cat_c to the top of the list). Both the categories and the s...