similar to: R limits documented?

Hi All, I need to evaluate a series expansion using Legendre polynomials. Using the 'orthopolinom' package I can get a list of the first n Legendre polynomials as character strings. > library(orthopolynom) > l<-legendre.polynomials(4) > l [[1]] 1 [[2]] x [[3]] -0.5 + 1.5*x^2 [[4]] -1.5*x + 2.5*x^3 [[5]] 0.375 - 3.75*x^2 + 4.375*x^4 But I can't figure out how to

Dear list, This is quite a specific question requiring the package orthopolynom. This package provides a nice implementation of the Legendre polynomials, however I need the associated Legendre polynomial which can be readily expressed in terms of the mth order derivative of the corresponding Legendre polynomial. (For the curious, I'm trying to calculate spherical harmonics [*]).

Hi all, We know that Hermite polynomial is for Gaussian, Laguerre polynomial for Exponential distribution, Legendre polynomial for uniform distribution, Jacobi polynomial for Beta distribution. Does anyone know which kind of polynomial deals with the log-normal, Student抯 t, Inverse gamma and Fisher抯 F distribution? Thank you in advance! David [[alternative HTML version deleted]]

Hello everyone, I would like to find out if there are already implemented function for legendre polynomials. I tried google but returns nothing. How do you suggest me to search for that? Regards Alex [[alternative HTML version deleted]]

Have you ever worked in R with bivariate polynomials? How did you implement simple operators like addition/multiplication? I found a package called multipol that seems to support these kinds of operators but I do keep receiving error. Check for example the following snippet of code (you can copy & paste) require('orthopolynom') require('polynom') require('multipol')

Dear R-help, I have fitted a glm logistic function to dichotomous forced choices responses varying according to time interval between two stimulus. x values are time separation in miliseconds, and the y values are proportion responses for one of the stimulus. Now I am trying to extrapolate x values for the y value (proportion) at .25, .5, and .75. I have tried several predict parameters, and they

The search at www.r-project.org mentioned a function "gauss.hermite{rmutil}". However, 'install.packages("rmutil")' produced, 'No package "rmutil" on CRAN.' How can I find the current status of "gauss.hermite" and "rmutil"? Thanks, Spencer Graves

Can anyone help me on how to get the nodes and weights of the adaptive quadrature using R. Best wishes Boikanyo. ----- The University of Glasgow, charity number SC004401

Good day everyone, I want to use the Gram-Charlier series expansion to model some data. To do that, I need functions to: 1) Calculate 'n' moments from given data 2) Transform 'n' moments to 'n' central moments, or 3) Transform 'n' moments to 'n' cumulants 4) Calculate a number of Hermite polynomials Are there R-functions to do any of the above?

Which function implements the piecewise cubic Hermite interpolation? I am looking for equivalent of matlab's interp1 with the method = 'pchip' Here is the reference http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/ref/interp1.html& -- View this message in context:

Hi, I am trying to find a function that returns simply the weights and points of an n point gauss hermite integeration, so that I can use them to fit a non-standard likelihood. I have found some documentation for the function 'gauss.hermite' written by jim lindley, but can't find the actual binary on CRAN I'm aware there are lots of functions like glmm, glmmML etc to fit mixed

Hi All, I am trying to use A Gaussian quadrature over the interval (-infty,infty) with weighting function W(x)=exp(-(x-mu)^2/sigma) to estimate an integral. Is there a way to do it in R? Is there a function already implemented which uses such weighting function. I have been searching in the statmode package and I found the function "gauss.quad(100, kind="hermite")" which uses

Does anyone know how to do hermite or Bezier splines in R? I can find Matlab routines, but really need to implement them in R. Failing that I'd be interested in other conformal splines. I need to smooth and interpolate animal tracking data. Antarctic Wildlife Research Unit School of Zoology University of Tasmania PO Box 252-05 Hobart TAS, 7001 Australia Phone: (0)3 6226 2645 Fax:

Hi all, I am using the 'gaussHermite' function from the 'pracma' library ############ CODES ########### library(pracma) cc=gaussHermite(10) cc$x^2 cc$x^5 cc$x^4 ############ CODES ########### as far so good. However, it does NOT work for any NON integer values, say ############ CODES ########### cc$x^(2.5) cc$x^(-2.5) ############ CODES ########### But just think about it

Hi all, Does anybody know any function that performs gaussian adapative quadrature integration of univariate functions? Thanks in advance, Regards, Caio __________________________________________________ [[alternative HTML version deleted]]

Does anyone see why my code does not integrate to 1? library(statmod) mu <- 0 s <- 1 Q <- 5 qq <- gauss.quad(Q, kind='hermite') sum((1/(s*sqrt(2*pi))) * exp(-((qq$nodes-mu)^2/(2*s^2))) * qq$weights) ### This does what's it is supposed to myNorm <- function(theta) (1/(s*sqrt(2*pi))) * exp(-((theta-mu)^2/(2*s^2))) integrate(myNorm, -Inf, Inf)

Hi, I'm a student studing for Math. & Infor. Ing. in Tirana,Albania and a have a final project in R to finish in a week, so I badly need your help... The topic of the project is "Hermite Interpolation" and a I have allready done a script that finds the approximation in a certan point x, H(x) ~f(x) but i want to find the value of his derivative H'(x)~f'(x) as well and to

Hello, I have been using the package "spdep" to run spatial regressions on a data set with about 2500 observations. It has performed well up until now, but the following code resulted in an error: > load("Panel.90s.ok.R") > attach(Panel.90s.ok) > neighs<-dnearneigh(cbind(x,y),0,50000) > help(nbdists) > dists<-nbdists(neighs,cbind(x,y)) >

I have a function written for Splus, when I run it in R I obtain get an error because the function has the elements "0.d0" and "2.d0". How can I change it to run in R? The function can be found in page 230 from http://www.stat.wisc.edu/~mchung/teaching/stat471/stat_computing.pdf Function is as follows: gauher <- function(n) {# Gauss-Hermite: returns x,w so that

I've written a series of functions that evaluates an integral from -inf to a or b to +inf using equally spaced quadrature points along a normal distribution from -10 to +10 moving in increments of .01. These functions are working and give very good approximations, but I think they are computationally wasteful as I am evaluating the function at *many* points. Instead, I would prefer to use