similar to: evolution of Nelder-Mead process

Dear list, ? I am trying to program semi-random movement within a circle, with no particles leaving the circle. I would like them to bounce back when they come to close to the wall, but?I don't seem to be able to get this right. ?Would somebody?be able to?give me a hint ? This is my code so far, the particle starts at some point and moves towards the wall, but I don't get the

Dear Jim and Henrique, thank you both for your help. I have done this but run into another problem: ? In the example?below "loc1,loc2" occurs in the (now correct, thanks to your advice) "list" twice. ? ? trips=("loc1,loc2","loc2,loc3") ? DF$listoftrips=("loc1,loc2", "loc1,loc3", "loc2,loc3","loc1,loc2"). ? I?am

Dear list, I would like to create a time series plot in which the paths of several individuals are stacked above each other, with the x-axis being the total observation period of three years ( 1.1.2004 to 31.12.2007) and the y-axis being some defined range[min,max]. My data consist of Date/Time information and the paths of 45 individual as the distance from the location of release. An example

Dear list,   Dear list, I am using read.csv.sql() from the sqldf package to read individual-based data from a csv file that is too large for R. My original file contains a column called “ID” that identifies the individual. I would like to read in data for only one individual at a time, for example "Bobby". read.csv.sql("filename",sql = 'select * from file where ID =

Dear list, ? I am using match() to match pairs of locations, e.g. trip="loc1,loc2" from a list of such pairs, e.g. list=("loc1,loc2", "loc1,loc3", "loc2,loc3","loc2,loc1"). ? In this example match() will match "trip" with the first element of "list", but not the 4th, because the order is reversed. ? How can I get a match with

Dear members, How can I read and plot an ArcGIS raster file into R ? The file has extension .aux and contains floating point bathymetry data. The purpose is to create a spatial model in R that uses ArcGIS map data. I have managed to read and plot various shape files into my R project, but I am stuck with this now. I am new to this list and also to R, so any help would be much appreciated. Many

Dear list, ? would anybody be able to tell me why the statement ? Tripstatistics=aggregate(TripsData[2:3],by=list(Trip=Tripmatch),FUN="mean") ? seems to work well with TripsData 1 but not with TripsData 2 ? ? With TripsData 2 it yields ? Error in FUN(X[[1L]], ...) : arguments must have same length I can't see a difference in the two data sets. Could someone shed light on the error

Dear list, I am trying to program semi-random movement within a circle, with no particles leaving the circle. I would like them to bounce back when they come to close to the wall, but I don't seem to be able to get this right. Would somebody kindly give me a hint ? This is my code so far, the particle starts at some point and moves towards the wall, but I don't get the "bouncing

Hi, I have written an R translation of C.T. Kelley's Matlab version of the Nelder-Mead algorithm. This algorithm is discussed in detail in his book "Iterative methods for optimization" (SIAM 1999, Chapter 8). I have tested this relatively extensively on a number of smooth and non-smooth problems. It performs well, in general, and it almost always outperforms optim's

All, In looking at `optim', it doesn't appear that it is possible to impose nonlinear constraints on Nelder- Mead. I am sufficiently motivated to try to code something in C from scratch and try to call it from R.... Does anyone have some good references to barrier and/or penalization methods for Nelder-Mead? I would ideally like some papers with pseudocode for method(s) that are in

Dear UseRs, Is there a way to define the lower-upper bounds for parameters fitted by optim using the Nelder-Mead method ? Thanks, Arnaud [[alternative HTML version deleted]]

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 all, I?m having some problems getting optim with method="Nelder-Mead" to work properly. It seems like there is no way of controlling the step size, and the step size seems to depend on the *difference* between the initial values, which makes no sense. Example: f=function(xy, mu1, mu2) { print(xy) dnorm(xy[1]-mu1)*dnorm(xy[2]-mu2) } f1=function(xy) -f(xy, 0,

Hello everybody, I have a matrix with measurement values and plot them with persp. I want to highlight different heights in different colors. At least everything above and under a certain z-level shall have a different color to make the differences in height more obvious. How can I do that or do I have to use another package? Best regards, Juliane

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Today we became aware of a bug in the Icecast code handling source client URL-authentication and are releasing a security fix. The bug was discovered by Juliane Holzt, who we'd like to thank for bringing this to our attention and providing us with further details. Affected Icecast versions: 2.3.3(first release with stream_auth) 2.4.0 2.4.1 Fix

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Today we became aware of a bug in the Icecast code handling source client URL-authentication and are releasing a security fix. The bug was discovered by Juliane Holzt, who we'd like to thank for bringing this to our attention and providing us with further details. Affected Icecast versions: 2.3.3(first release with stream_auth) 2.4.0 2.4.1 Fix

Dear R-users, we are happy to announce the release of our R package parcor. The package contains tools to estimate the matrix of partial correlations based on different regularized regression methods: Lasso, adaptive Lasso, PLS, and Ridge Regression. In addition, parcor provides cross-validation based model selection for Lasso, adaptive Lasso and Ridge Regression. More details can be found

Dear R-users, we are happy to announce the release of our R package parcor. The package contains tools to estimate the matrix of partial correlations based on different regularized regression methods: Lasso, adaptive Lasso, PLS, and Ridge Regression. In addition, parcor provides cross-validation based model selection for Lasso, adaptive Lasso and Ridge Regression. More details can be found

hello, i cant find a solution on this (might be) easy problem: i have a time serie by carlandar weeks, so for every carlendar week i have a value. now i would like to use the functions for time series, so i change structur to a time serie with cam <- ts(number,start=c(2001,1),deltat=7/365) or cam <- ts(number,start=c(2001,1),frequency=52) the problem on it is, that 2004 had 53 calendar

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