search for: maximas

I''m looking to write a javascript heavy clientside program with a something serverside backend that connects to the free maxima math program. I have extensive knowledge of ruby on rails, so I would prefer to call Maxima with ruby, but I don''t know if this is even possible. Its fairly easy to call Maxima (with a lisp implementation) using ANSI C, it is a little less easy to

Hello, I'm aware that recently there has been discussion of R joining forces with an algebra system in some way. Here is my $0.02. I suggest linking R with Maxima (http://maxima.sf.net). Maxima is written in Lisp. Maxima objects are pretty simple. Maxima works on expressions, and almost every expression is a Lisp list of the form ((op) arg1 arg2 arg3 ...) which associates an operator and

What is 1. par.ests <- optimfit$par 2. fisher <- hessb(negloglik, par.ests, maxvalue=maxima); 3. varcov <- solve(fisher); 4. par.ses <- sqrt(diag(varcov)); Thanks a lot, fit.GEV <- function(maxima) { sigma0 <- sqrt((6. * var(maxima))/pi) mu0 <- mean(maxima) - 0.57722 * sigma0 xi0 <- 0.1 theta <- c(xi0, mu0, sigma0) #10/5/2007: removed assign() for maxima.nl

If a run a LOESS model and then produce a smoothed surface: Is there any way to determine the coordinates of the local maxima on the surface? [[alternative HTML version deleted]]

...ith distr package and UnivarMixingDistribution function. Also I?m not able to install distr package because of an error. Can you create an example by rnorm function? or use dput to share x and y outputs of UnivarMixingDistribution function and I can look for the issue. Also You might have multiple maximas has same maximum y-values (for instance, y = sin(x)) and this definition is relevant to defined interval. For instance again, we can talk about a global extremum for a function like y = ax^2+bx + c. We know we will have only a single extremum point (maxima or minima). For higher order functions, we...

Hi, Thanks for your mail, and time It is not working for some arguments, when mean value is like >6. case mc0 <- c(0.08844446,0.1744455,0.1379778,0.1209769,0.1573065,0. 1134463,0.2074027) rv <-UnivarMixingDistribution(Norm(486.4255, 53.24133), Norm(664.0713, 3.674773), Norm(669.0484, 4.101381),

Hi I have a large dataset which follows a multimodal distribution. And I would like to identify the maxima. As the data is obtained from a stochastic simulation, not all maxima in the data are "real maxima of the dirstribution" but rather small random fluctuations. Unfortunately, it is not possible for me to run more simulations to smooth the obtained distribution. What I am doing

...sity(my.instance)$y )] value at > max. > [1] 0.02035133 > > > > > > > an you create an example by rnorm function? or use dput to share x and y > outputs of UnivarMixingDistribution function and I can look for the issue. > > > > Also You might have multiple maximas has same maximum y-values (for > instance, y = sin(x)) and this definition is relevant to defined interval. > For instance again, we can talk about a global extremum for a function like > y = ax^2+bx + c. We know we will have only a single extremum point (maxima > or minima). For higher...

Dear all, suppose I have a bi-variate function f(x,y), I want to find the maxima. I define x and y vector, and get matrix z=f(x,y). how can I get which (x0,y0) makes z become the maxima? I can do two loops to get the x0 and y0, but I think there may exist a function to do this.

Dear all, I wonder which R algorithm could perform a search of local maxima in an spatial grid, in other words, having the coordinates of a map (x,y,z... up to 6 coordinates) and then the altitude/height at each point (h) (in total 7 numerical variables) I would like to localise the peaks (local maxima) of that topological surface. Which R algorithm can perform this? Thanks a lot, Josep Maria,

Dear Niharika, As I said before, the problem is basically an optimization issue. You should isolate the problematic part from the rest of your study. Sometimes, more information does not help to solution. All the answers from us (Ulrik, David, me) are more or less are correct to find a maximum point. Newton?s method is also correct. But after answers, you only say, it didn?t find the right

Hi. Suppose I have a vector that I partition into disjoint, contiguous subvectors. For example, let v = c(1,4,2,6,7,5), partition it into three subvectors, v1 = v[1:3], v2 = v[4], v3 = v[5:6]. I want to find the maximum element of each subvector. In this example, max(v1) is 4, max(v2) is 6, max(v3) is 7. If I knew that the successive subvector maxima would never decrease, as in the example,

Hi, I've been following the list for a few months but this just my first post to the list. I've just started to use compiz again a few days ago and I have a few things (probably bugs) here that bugged me a little bit. I am not sure whether the bugs is in compiz or somewhere else so it would be nice if someone could confirm them. Here they are: - on default window decoration the maximize

I have not followed the history of this thread, but I am quite flummoxed as to why the OP is rewriting code to estimate parameters from an univariate Gaussian mixture model when alternatives such as EMCluster (which generally appears to handle initialization better than MClust) exist. Or perhaps there is more to it in which case I apologize. But I thought that I would make the OP aware of the

>From time to time people request symbolic computations beyond what D() and deriv() etc can provide. A brief look at the internet shows that there are many more or less developed computer algebra packages freely available. Therefore, I wondered if it would be an idea to try to 'integrate' one of these packages in R, which I guess can be done in more or less elegant ways... I do not know

I have data in the form of (x,y) pairs and would like to find local minima and maxima (typically the zeros of the 2nd derivative) of the y values. I looked at numericDeriv, but I don't have an "expression" per se. I looked at optim, also, but it looks like it will find only one "global" max or min. I can code up my own piecewise derivatives, but wondered if there is

Hi there, I use the surf.gls() function to fit a variable measured over a surface. When I plot the predicted surface, there are local minima/maxima in almost every coordinate where data were measured, which seems aberrant. For instance: ?? x <- c(343,293,343,243,293,343,443,543,593,243,293,343,393,443,493,543,593,143,193,243,293,343,393,443,

I have a Gaussian mixture model with some parameters mean=(506.8644,672.8448,829.902) sigma=(61.02859,9.149168,74.84682) c=(0.1241933, 0.6329082, 0.2428986) And the plot look something like below.[image: enter image description here] <https://i.stack.imgur.com/4uUQ9.png> Also, if I change my parameters to mean=(2.15,2.0,2.9) sigma=(0.1,0.1,0.1) c=(1/3,1/3,1/3) Then plot would change

Please keep the list in cc. Sorry, it didn't work as expected. Maybe someone else have an appropriate solution. Best, Ulrik On Sa., 26. Aug. 2017, 12:57 niharika singhal <niharikasinghal1990 at gmail.com> wrote: > Hi > > Thanks for you mail, > I really appreciate your time on my problem > > I have posted this problem on > > >

Dear R users, I have created a Loess surface in R, in which x is relative longitude by miles, y is relative latitude by miles, and z is population density at the neighborhood level. The purpose is to identify some population centers in the region. I'm wondering if there is a way to determine the coordinates (x,y) of each center, so I can know exactly where they are. Let me use the