similar to: Simplex function in R

Hi List I want to carry out structural mode. Following Example l have taken from Basic Econometrics- Damodar Gujarati : Advertising intensity function: Ad/S = a0 + a1M + a2 (CD/S) + a3C + a4C2 + a5Gr + a6Dur – (1) Concentration function: C = b0 + b1 (Ad/S) + b2 (MES/S) -(2) Price-cost margin function: M = c0 + c1(K/S) + c2Gr + c3C + c4GD + c5(Ad/S) + c6 (MES/S)

Hello, In R I am trying to use Kalman filtering to find a solution for an hydrological problem. With Kalman Filtering I want to estimate the discharge comming from three storage bassins. I have programmed a function in R which can run KalmanSmooth. When I'm asking for the function and putting in values, R detects the following error: "Error in as.vector(data) : Argument "S1" is

Hi, I have a financial (zoo) time series with prices and volumes (although I can get the coredata as a matrix). Due to the data-source some indices have multiple observations. I want to aggregate these according to a weighted average. 11:00:01 34 1000 11:00:01 35 500 11:00:01 35 1000 11:00:02 34 500 11:00:02 35 500 should become 11:00:01 34.6 2500 11:00:02 34.5 1000 I currently do this

Hello, Can anyone explain the following behaviour? To me it seems a bug, but maybe it is intentional. It seems that a diff on a zooreg class that is not _strictly_ regular only considers those entries that are 'deltat' apart. In the following, diff on the zooreg class only returns values where the index was one second apart. The example replicates by dev code, but I've also tested

To Whom It May Concern: The following appears to be a bug in the way POSIXct dates are formated. The example is forced, but occurs naturally when importing Excel type dates (where fractional part is fraction of a day) and small rounding errors result. As shown, looking at the POSIXct class, it looks as if both times are 16:11:03 (truncation) Looking at as.numeric.POSIXct, it looks as if

Hello, I have the following problem: I have a set of n matrix equations in the form of : [b1] = [A] * [b0] [b2] = [A] * [b1] etc. vertical vectors [b0], [b1], ... are GIVEN. We try to estimate matrix A. As there are many equations (more than cells in matrix A) the system has no solutions. A is transition matrix (stochastic matrix) or markov process, so the sum of each row = 1 and each entry is

x<-matrix(c(1,0,0,0,1,0,0,0,1),nrow=3) > y<-matrix(c(0,0,0,1,0,0,1,1,0),nrow=3) > z<-matrix(c(0,1,0,0,1,0,1,0,0),nrow=3) > x[z]<-y[z] The resultant matrix x is all zeros except for the last two diagonal cells which are 1's. While y is lower triangualr 0's with the remaining cells all ones. I really don't understand how this deceptively simple looking piece of

Hello, I have just started using R, and have found it quite easy to make plots of probability densities for normal and beta distributions, etc. Now, I'm looking at trying to make a simplex plot of a Dirichlet density, but have gotten stuck and was hoping that someone could help. Ideally, the plot would look something like the 3d plots on Wikipedia here:

Dear R users, Is anyone familiar with the "n.iter" argument of the simplex() function (in the boot package)? It seems it doesn't have an effect no matter what value I set it ... I'm trying to solve a linear programming problem and running into the problem of simplex.object$solved = 0 or "A value of 0 indicates that the maximum number of iterations was reached without

Full_Name: George F. LeCompte Version: 1.6.1 OS: Windows 98 Submission from: (NULL) (208.8.162.161) This may be a newbie problem. I am attempting tor unt the simplex routine from the boot package. The example code doesn't find simplex. What's wrong here? > help(simplex,package=boot) > # from the resulting article > > # This example is taken from Exercise 7.5 of

I'm exploring the simplex algorithm with a simple transportation problem of the form: minimize: 8a + 6b + 10c + 9d + 5e + 7f subject to the constraints: a + b + c = 11 d + e + f = 14 a + d = 10 b + e = 8 c + f = 7 I've implemented this in R (1.4.0 (2001-12-19), SunOS 5.7) as: require(boot) costs = c(8,6,10,9,5,7) constraints = c( 1,1,1,0,0,0, 0,0,0,1,1,1, 1,0,0,1,0,0,

I am running the following code (testing the use of the simplex function to determine if a point is in the convex hull of another set of points or not): >a <- c(0, 0) >A3 <-matrix(c(1,2,3,4,1,1), ncol = 2, byrow = T) >b3 <-c(1.5, 3.5, 1) >simplex(a = a, A3 = A3, b3 = b3) and the following error message appears: Error in simplex1(out1$a[1:(n + m1 + m2)], out1$A[, 1:(n + m1

In trying to use simplex() from the boot package, I have run into a situation that doesn't seem like it should be possible. It is claiming that it has solved the LP, but returns a vector of all zeros, which does not satisfy the constraints I passed in. A small example: > ubMatrix <- matrix(c(1,1,-1,0,-1,-1), 3, 2) > ubVector <- c(2,1,-1) > objective <- c(0,1) >

I am interested in using the nonlinear forecasting techniques developed by Sugihara et al. In particular the simplex projection and the S-Map (see this website for details and reprints: http://iod.ucsd.edu/simplex/ ). I've looked through CRAN but could not find any package with functions that allow such analysis. Any pointers? Thanks, Manu

Hello, anyone knows if there is a way in R to draw contour on a simplex based on a function f(x,y,z) with domain (x+y+z = 1)? Thank you! gigi [[alternative HTML version deleted]]

Hi, I need some help. I'm doing a project that demands me to obtain several simplex solutions and I would like to can keep the solution in a vector or something to be able to use it after I get it. The comand simplex() prints the solution but how can I keep it? Another alternative would be to export it to excel, how can I do this? I just see the solution and have to note it on a paper or

Greetings! I want to follow the evolution of a Nelder-Mead function minimisation (a function of 2 variables). Hence each simplex will have 3 vertices. Therefore I would like to have a function which can output the coordinates of the 3 vertices after each new simplex is generated. However, there seems to be no way (which I can detect) of extracting this information from optim() (the

Hello everybody. I found out the other day something quite astonishing (which I guess is not astonishing at all to those in the know): in d-dimensional space, determining whether a given point is inside the convex hull of a set of n points is elegantly and quickly solvable using linear programming. If the columns of matrix "ff" are the coordinates of the set of points, then in d=2

Hello The excellent adapt package integrates over multi-dimensional hypercubes. I want to integrate over a multidimensional simplex. Has anyone implemented such a thing in R? I can transform an n-simplex to a hyperrectangle but the Jacobian is a rapidly-varying (and very lopsided) function and this is making adapt() slow. [ A \dfn{simplex} is an n-dimensional analogue of a triangle or

Hello, I am working on a trixbox based system with a TDM410P connected to 3 phone lines from the CO. The asterisk box is on a full duplex 100Mb LAN with some polycom and Aastra SIP phones. In general everything works. the problem I am trying to solve is that if both parties to a call speak at the same time one of the voices gets cut out such that the talker A cannot hear what talker B is