similar to: Bivariate polynomials in R

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 [*]).

Good Evening, I would like to work with multivariate polynomials (x and y variables). I know that there is a package called multipol but I am not sure that supports my needs. I use a function (in reality legendre.polynomials) which creates me the polynomials I want. For example the following returns > legendre.polynomials(2)[[2]] x (first order polynomial) I would like to calculate the

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

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]]

Hello Dear List members, as you can see (and guess) from the code below adaptIntegrate(f,lowerLimit=c(-1,-1),upperLimit=c(.9999,.9999)) $integral [1] 9.997e-09 $error [1] 1.665168e-16 $functionEvaluations [1] 17 $returnCode [1] 0 > adaptIntegrate(f,lowerLimit=c(-1,-1),upperLimit=c(1,1)) the last command runs for 45 mins now. -this one takes only less than sec:

Dear All, I have found in the poly help this sentence: The orthogonal polynomial is summarized by the coefficients, which can be used to evaluate it via the three-term recursion given in Kennedy & Gentle (1980, pp. 343–4), and used in the predict part of the code. My question: which type of orthogonal polynomials are used by this function? Hrmite, legendre.. TIA Giovanni [[alternative HTML

Hello List please find a new package, multipol, recently uploaded to CRAN. This package generalizes the polynom package (which handles univariate polynomials) to the multivariate case. A short article discussing the package will appear in the next issue of Rnews, Insha'Allah enjoy -- Robin Hankin Uncertainty Analyst and Neutral Theorist, National Oceanography Centre, Southampton

hits=1.0 tests=MANY_EXCLAMATIONS X-USF-Spam-Flag: NO Hi I am writing a package for multivariate polynomials ('multipols') using S3 methods. The package includes a Ops.multipol() function for the arithmetic methods; I would like to define some sort of user-specified Boolean option which, if set, would force results to be simplified as they are produced. Call this option

Is there documentation on R limits? That is, max matrix size, etc.? Diagnostics when limits are exceeded are not always meaningful. For example: > x <- rep(0,50000*50000) Error in rep(0, 50000 * 50000) : invalid 'times' argument In addition: Warning message: In as.vector(data) : NAs introduced by coercion Here's another example: > library(orthopolynom) > hermite <-

I am writing a package and need to decide whether to use S3 or S4. I have a single class, "multipol"; this needs methods for "[" and "[<-" and I also need a print (or show) method and methods for arithmetic +- */^. In S4, an object of class "multipol" has one slot that holds an array. Objects of class "multipol" require specific arithmetic

Hi: I am using the package "KernSmooth" to do the local polynomial regression. However, it seems the function "locpoly" can only deal with univariate covaraite. I wonder is there any kernel smoothing package in R can deal with bivariate covariates? I also checked the package "lcofit" in which function "lcofit" can indeed deal with bivariate case. The

Dear list, I'm seeking some advice regarding a particular numerical integration I wish to perform. The integrand f takes two real arguments x and y and returns a vector of constant length N. The range of integration is [0, infty) for x and [a,b] (finite) for y. Since the integrand has values in R^N I did not find a built-in function to perform numerical quadrature, so I wrote my own after

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]]

I am trying to use the cca/rda/capscale functions in vegan to analyse genetic distance data ( provided as a dist object calculated using dist.genpop in package adegenet) with geographic distance partialled out ( provided as a distance object using dist function in veganthis method is attempting to follow the method used by Geffen et al 2004 as suggested by Legendre and . FORTIN (2010). I

Pierre Legendre has developed a beta version of a new redundancy analysis package called RdaTest that is available on his web page at the Universit® de Montréal. The test example that is included with the package is based on the example provided in his book (Numerical Ecology, Chapter 11 (Legendre & Legendre 1998)) I have downloaded the package and am attempting to run it so that I might

Hi, I would like to solve a double integral of the form \int_0^1 \int_0^1 x*y dx dy using Gauss Quadrature. I know that I can use R's integrate function to calculate it: integrate(function(y) { sapply(y, function(y) { integrate(function(x) x*y, 0, 1)$value }) }, 0, 1) but I would like to use Gauss Quadrature to do it. I have written the following code (using R's statmod package)

Hi Folks! Im using the function poly to generate orthogonal polynomials, but Id like to see the actual polynomials so that I could convert it to a polynomial in my original variable. Is that possible and if so how do I do it? /E

Does anybody know of any R functions to perform chronological clustering as explained in: Legendre, P., S. Dallot & L. Legendre. 1985. Succession of species within a community: chronological clustering, with applications to marine and freshwater zooplankton. American Naturalist 125: 257-288. http://www.fas.umontreal.ca/BIOL/legendre/reprints/succession_of_species.pdf Thanks, Angel

This very likely falls in the category of an unexpected result due to user ignorance. I generated the following data: time <- 0:10 set.seed(4302007) y <- 268 + -9*time + .4*(time^2) + rnorm(11, 0, .1) I then fit models using both orthogonal and raw polynomials: fit1 <- lm(y ~ poly(time, 2)) fit2 <- lm(y ~ poly(time, degree=2, raw=TRUE)) > predict(fit1, data.frame(time =

Looking to the wonderful statistical advice that this group can offer. In behavioral science applications of stats, we are often introduced to coefficients for orthogonal polynomials that are nice integers. For instance, Kirk's experimental design book presents the following coefficients for p=4: Linear -3 -1 1 3 Quadratic 1 -1 -1 1 Cubic -1 3 -3 1 In R orthogonal