search for: parabole

Dear all, I need your advice since I am looking for an implementation of the parabolic cylinder function in R. I found implemantations of the hypergemetric functions (the Whittaker and the confluent hypogeometric functions) in the package fAsianOptions but the parabolic cylinder function was unfortunately not there. Do you know of such implementation? Thank you very much for your advice.

Dear R users and experts, I want to fit a shifted parabolic function with the following functional form to my data: f(x)=a0*(x+a1)^2+a2 (a0, a1 and a2 are scaling factors.) What is standard approach to do this in R? I tried the "lm" function in R but I got problems getting the above functional form. Any help is welcome :) . Greetings, Henri

Hi all, i''m new at LARTC, and after reading the docs I found no solution to my problem ... On one side I have eth0 conected to the LAN, on the other side I have eth1 conected to a switch and to 3 DSL routers with 3 diferent providers, and also eth2 conected to a cisco 2600 conected to a LDMS line. I have readed the larct docs about multihomed conections to internet, but I''m

Dear all, Does any know how to solve PDE with R? The archive list refers to the use of ODE if PDE are parabolic. I am not a mathematician and this does not mean anything for me! help would be very appreciated. Many thanks -- ___________________________________________________ Christophe NGUYEN UMR 1220 INRA-ENITAB Transfert sol-plante et cycle des ?l?ments min?raux dans les ?cosyst?mes

Hi, I've got a matrix, Z, of values representing (as it happens) optical power at each pixel location. Since I know in advance I've got a single, convex peak, I would like to do a 2D parabolic fit of the form Z = poly((x+y),2) where x and y are the x,y coordinates of each pixel (or equivalently, the row, column numbers). Is there an R function that lets me easily implement that?

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Rers: I have some ecological data (stream velocity vs. % cover of submerged weeds) that shows strong evidence of a thresholding step-function, e.g. below some velocity, % cover ranges from 0% to 100% (with no apparent relationship to velocity within this range of velocities), but above a certain "threshold" velocity, the % cover does not appear to exceed, say, 10%. There are good

I have an array of floating-point measurements on a square (5 by 5) 2d grid. The data are nominally constant, and somewhat noisy. I need to find any significant spatial trend, e.g. bigger on the left, bigger in the middle, etc. I have many thousands of these data sets that need to be scanned for 'interesting' spatial variations, selecting the datasets that are beyond some criterion of

Dear List: I have a data frame prepared in the couting process style for including a binary time-dependent covariate. The first few rows look like this. PtNo Start End Status Imp 1 1 0 608.0 0 0 2 2 0 513.0 0 0 3 2 513 887.0 0 1 4 3 0 57.0 0 0 5 3 57 604.0 0 1 6 4 0 150.0 1 0 The outcome

Hi, everyone I am trying to estimate 3 parameters for my survival function. It's very complicated. The negative loglikelihood function is: l<- function(m1,m2,b) -sum( d*( log(m1) + log(m2) + log(1- exp(-(b + m2)*t)) ) + (m1/b - d)*log(m2 + b*exp(-(b + m2)*t) ) + m1*t - m1/b*log(b+m2) ) here d and t are given, "sum" means sum over these two vairables. the parameters

Hello, I want to solve some two dimensional equation system with R. Some systems are not solvable analytically. Here is an example: (I) 1/n*sum{from_i=1_to_n}(Xi) = ln lambda + digamma(c) (II) mean(X) = x / lambda I want to find lambda and c, which R-function could do that task? Carsten [[alternative HTML version deleted]]

Sorry, For me a vector is a matrix with mx1 dimmensions. But it is true that it is not the way I correctly must talk in R. Can you guide me in what I?m trying to do? I?m trying to find what I want in Excel using something like a parabolic function but dind?t get yet (then to try to replicate in R). 2017-06-02 7:01 GMT+02:00 Bert Gunter <bgunter.4567 at gmail.com>: > Bert Gunter >

Subject: Eliminate repeated components from a vector X-Mailer: VM 7.00 under 21.4 (patch 6) "Common Lisp" XEmacs Lucid Reply-To: fjmolina at lbl.gov FCC: /home/f/.xemacs/mail/sent Does anyone know how I can eliminate repeated elements from a vector?

Hi, I'm using R to find esplicit functions fitting set of data. The data contains about 30 points, which have different weights (number of cases represented from the point). I plot the points, choose "by eye" a function made with exp or arctg or polinomial and use nlm to minimaze the root mean error with correct the weights. For Example: Err <- function(p) sum((weight*(y

Is there a package in R which implements numerically solves pde ? Thanks, Tolga

Hi, anyone knows about any functions in R can get multidimensional integration not over a multidimensional rectangle (not adapt). For example, I tried the following function f(x,n)=x^n/n! phi.fun<-function(x,n) { if (n==1) { x }else{ integrate(phi.fun, lower=0, upper=x, n=n-1)$value } } I could get f(4,2)=4^2/2!=8, but failed in f(4,3)=4^3/3! Thanks Best, Lynette

Hello, I'm hoping for some help implementing a general optimization problem in R. I'd like to write a program that for a vector of non-negative input values, x, returns a non-negative "normalized" vector y such that sum(y)==1, and y <= maxx (vector of maximum values), and for which sum((x-y)^2) is minimized. Additionally, I'd like to remove (0,minx) from the domain of each

which is the purpose of this functions? _________________________________________________________________ Busca desde cualquier p?gina Web con una protecci?n excepcional. Consigue la Barra de herramientas de Windows Live hoy mismo y GRATUITAMENTE. http://www.toolbar.live.com -------------- next part -------------- An HTML attachment was scrubbed... URL:

Dear all, I'm trying to produce a log-likelihood profile for a GPD estimate with the ismev package. When following the examples, everything is working fine, i.e. I get a nice parabolic log-likelihood curve. When using my own data (intensity of hurricanes at landfall), the log-likelihood curve looks like a step function. Am I doing something wrong here? Is my data not suited for the GPD fit?

Hi R-users, I am using arima to fit a time series. Now I would like to include an intervention component "It (0 before intervention, 1 after)" using different types of impacts, that is, not only trying the simple abrupt permanent impact (yt = w It ) with the xreg option but also trying with a gradual permanent impact (yt= d * yt-1 + w * It ), following the filosophy of Box and Tiao