similar to: Multivariate polynomials Howto

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 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 [*]).

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]]

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

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

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

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

Hi, I want to calculate the bandwith of a multivariate local polynomial regression such as the model is: Y=m(X,Z)+u. Please, somebody knows how I can do it in a multivariate case? In an univariate case I use the instrucction "regband" of the locfit package, but it is impossible to find a way to do it in the bivariate case. Please, help me. Thanks you in advance Alexandra

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

Hello, I am trying to estimate a multivariate regression of Y on X with regression splines. Y is (nx1), and X is (nxd), with d>1. I assume the data is generated by some unknown regression function f(X), as in Y = f(X) + u, where u is some well-behaved regression error. I want to estimate f(X) via regression splines (tensor product splines). Then, I want to get the predicted values for some new

Dear R-Help Does "The R Package for Multivariate and Spatial Analysis Version 4.0 (Casgrain and Legendre, 2001)" exist on CRAN and under what name? It supposedly has a chronological clustering program ,CHRONO, that I would like to use. Alternatively, I would ask if there is a R based program that performs chronological clustering? Thanks Alex Alex Hanke Department of Fisheries and

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]]

Dear All, I have analysed time to event data for continuous variables by considering the multivariable fractional polynomial (MFP) model and comparing this to the untransformed and log transformed model to determine which transformation, if any, is best. This was possible as the Cox model was the underlying model. However, I am now at the situation where the assumption that the competing risks

Dear Keith, >>>>> <Keith.Jewell at campdenbri.co.uk> >>>>> on Thu, 16 Jul 2015 08:58:11 +0000 writes: > Dear R Core Team, > Last week I made a post to the R-help mailing list > ?predict.poly for multivariate data? > <https://stat.ethz.ch/pipermail/r-help/2015-July/430311.html> > but it has had no responses so I?m

Awaiting some suggestion. Was my question not very understandable? Please let me know how can I offer more elaborate clarification. Additionally, I would like to solve the determinant of "p1" for the values of "z" (I am working with some multivariate time series modelling). When I use det() function, it am getting error that, that function is not for objects with class

Hello to everybody, Somebody know how I can apply the instruction (regband) of the package (locfit) to a multivariate covariate. In the instructions states that the formula has to have only one predictor. How can I use that when I have an unknown function with two predictors, m(X,Z)? Is there any other way to get a bivariate bandwidth in a local regression polynomial? I'll appreciate any

Hi, I am looking for an R package that would calculate multivarite (mostly 2d and 3d, tensor) cubic interpolating splines, so that I could evaluate these splines (and their derivatives) at many points (unkown at the time of calculating the spline polynomials) repeatedly. To make things concrete, I have an array V with dim(V) = k and gridpoint vectors grid=list(...), length(grid[[i]])==k[i],

I'm looking for a way to solve a linear equation system where the factors are polynomials: Here is a simplified example (To solve my problem, I have to deal with dimensions larger than 2): ( s + 2) x1 + (s - 3) x2 = 2 ( s^2 + 2s - 1) x1 - 2 x2 = 1 Theoretically the solution is easy: By performing polynomial multiplications, divisions and sums. I found out, that R is able to

I'm trying to find a way to fit a polynomial of degree n in x and y to a set of x, y, and z data that I have and obtain the coefficients for the terms of the fitted polynomial. However, when I try to use the surf.ls function I'm getting odd results. > x <- seq(0, 10, length=50) > y <- x > f <- function (x, y) {x^2 + y} > library(spatial) > test <-

How can ordinary polynomial coefficients be calculated from an orthogonal polynomial fit? I'm trying to do something like find a,b,c,d from lm(billions ~ a+b*decade+c*decade^2+d*decade^3) but that gives: "Error in eval(expr, envir, enclos) : Object "a" not found" > decade <- c(1950, 1960, 1970, 1980, 1990) > billions <- c(3.5, 5, 7.5, 13, 40) > #