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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 Resear...

...ampaign.*Same thing i have done using agi and database,i never use queue management 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 age...

...levant 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 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...

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 ...

...e 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, the problem is to find A_0, A_1, ... A_p and "C" from the given sample, assuming the curve is like this: A_0*f_0(x)+A_1*f_1(x)+ ... + A_p*f_p(x) with x < C A_0'*f_0(x)+A_1'*f_1(x)+ ... + A_p'*f_p(x) with x >= C Functions f_1, f_2, ... f_p are known. Is there anything in R for that? I have tried to...

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_...

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

...1 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)==di...

...rix(nrow=30,ncol=54))*50 for (i in 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_DELT...

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 th...

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...

Hi, It is my understanding that the eigenvectors of a circulant matrix are given as follows: 1,omega,omega^2,....,omega^{p-1} where the matrix has dimension given by p x p and omega is one of p complex roots of unity. (See Bellman for an excellent discussion on this). The matrix created by the attached row and obtained using the following commands indicates no imaginary parts for the

...ve collinearity problems, so I decided to do a partial regression to predict y. I did it this way: - I regressed y to A, and calculated the residuals (e_y) (reg1) - I regressed x to A, and calculated the residuals (e_x) (reg2) - I regressed e_y to e_x (reg5) It looks like this: y = a_0 + a_1 A (reg1) x = b_0 + b_1 A (reg2) e_y = y - (a_0 + a_1 A) (3) e_x = x - (b_0 + b_1 A) (4) e_y = beta_0 + beta_1 e_x (reg5) Then, to predict a y_0 from a new x_0 and A_0, we would: Calculate e_x0 with the equation (4). Calculate e_y0 with the equation (reg5) and then: y_0 = e_y0 + (a_0 + a_1 A_0) Now...

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 this possible to do? Lep pozdrav / With regards, Gregor Gorjanc ---------------------------------------------------------...

...1.17, 0.426, 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 di...

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), and with the variance specified by something like sigma^2_t = exp(beta_t * X_t), where X_t is my exogenous variable. I would be very grateful if somebody could point me in the direction of a...

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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 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...

Hi, could anyone tell me how predict() predicts the new value(s), of a MA(1) arima-modell. its really easy to make it with an AR(1), knowing the last term, but how can i or R know the last error? It would also help if somebody could tell me how to find the "open" source of the function predict(). Thanks and sorry for my poor english. -- View this message in context: