similar to: rbind(NULL,NULL) and simplex()

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

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

I have a set of linear equations and would like to find any feasible solution. A simplex solution works in Case 1 below, but not in Case 2. I would be grateful for any help. Case 1: Find any feasible solution for the set of linear equations: a + b + c = 5 a + b + 0c = 4 0a + b + c = 4 Solution - a feasible (and unique) solution is a=1, b=3, c=1. The following R code

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,

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:

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

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

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

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

Dear list, Does anyone have a suggestion (or better still) code for sampling from the uniform distribution over the convex hull of a set of points? Many thanks and best wishes, Ranjan

Dear UseRs, I would like to know which function is the most efficient in finding convex hull of points in 3(or 2)-dimensional case? Functions for finding convex hull is the following: convex.hull (tripack), chull (grDevices), in.chull (sgeostat), convhulln (geometry), convexhull.xy (spatstat), calcConvexHull (PBSmapping). I also would like to know if there is a function that can be used

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 everyone, I wonder if there is a code in r that can generate a 3d convex hull from a data-frame containing 3 columns and then use another database with the same three columns and for each row determine if the xyz point is inside or not the convex hull generated with the first database? The package geometry allows to calculate a hull and it's volume. I was planning to calculate the volume

Dear R gurus and users, I seem to have problem finding the right tool for plotting convex hulls over 2D plots, after a cluster analysis. In fact I would like to draw a convex hull in 2D for a generic group of points. I found a "convhulln", but this doesn't seem to give me a convex hull. Here is what I do: > library(mvtnorm) > Mean <- c(2,1) > Sigma <-

Ranjan Maitra writes: > Does anyone have a suggestion (or better still) code for sampling > from the uniform distribution over the convex hull of a set of > points? This is implemented in library 'spatstat'. If x and y are vectors of coordinates of your initial set of points, library(spatstat) W <- convexhull.xy(x, y) P <- runifpoint(42, W) will compute

Hi, I seek to identify those points in/outside a multidimensional convex hull (geometry::convhulln). Any suggestions? Background just in case I'm going down a really wrong road: Given an observed data set with one dependent/observed variable (Y) and multiple (3 to 10) independent/design variables (X1, X2, ...) I want to increase the number of points by interpolating. I'm using

Hi there, I have been using the Tps function (within the Fields package) for a while now to interpolate different sedimentary units. Due to the method of formation of the units I know that at some edges the thickness of the unit decreases to zero. I was wondering if there was someway to specify that the interpolation only occurs within the convex hull of the data, outside of which the the values

Hi All, convhulln {geometry} computes the convex hull of a set of points in n- dimensions via .call, returning the hull itself, and also "unavoidably generates a diagnostic report on an Rterm console." See the example below. I need to access the results of the diagnostic report (specifically the computed hull volume) from within R, but I cannot see how. I've looked at