similar to: polynomial

Hi there, Does anyone know how I solve for x from a given y in a polynomial function? Here's some example code: ##example file a<-1:10 b<-c(1,2,2.5,3,3.5,4,6,7,7.5,8) po.lm<-lm(a~b+I(b^2)+I(b^3)+I(b^4)); summary(po.lm) (please ignore that the model is severely overfit- that's not the point). Let's say I want to solve for the value b where a = 5.5. Any thoughts? I did

Hi, I want find all roots for the following polynomial : a <- c(-0.07, 0.17); b <- c(1, -4); cc <- matrix(c(0.24, 0.00, -0.08, -0.31), 2); d <- matrix(c(0, 0, -0.13, -0.37), 2); e <- matrix(c(0.2, 0, -0.06, -0.34), 2) A1 <- diag(2) + a %*% t(b) + cc; A2 <- -cc + d; A3 <- -d + e; A4 <- -e fn <- function(z) { y <- diag(2) - A1*z - A2*z^2 - A3*z^3 - A4*z^4

Hi, I would like to know whether there exist algorithms to compute the coefficients or, at least, the degree of the minimal polynomial of a square matrix A (over the field of complex numbers)? I don't know whether this would require symbolic computation. If not, has any of the algorithms been implemented in R? Thanks very much, Ravi. P.S. Just for the sake of completeness, a

Dear R people: Is there a way to perform simple polynomial multiplication; that is, something like (x - 3) * (x + 3) = x^2 - 9, please? I looked in poly and polyroot and expression. There used to be a package that had this, maybe? thanks, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at

Hi, I would like to get the coefficient of polynomial expansion. For example, (1+ x)^2 = 1 + 2x + x^2, and the coefficients are 1, 2 and 1. (1 + x + x^2)^3 = 1 + 3*x + 6*x^2 + 7*x^3 + 6*x^4 + 3*x^5 + x^6, and the coefficients are 1, 3, 6, 7, 6, 3, and 1. I know that we can use polynom library. Is there any other way to do it without loading a library. Thanks a lot for your help. Peter

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

Full_Name: Tamas K Papp Version: 2.4.0 OS: linux Submission from: (NULL) (140.180.166.160) I was using the lines.polynomial method for plotting piecewise polynomials (parts of splines). I needed a feature to limit the range of plotting using a parameter given to the function (as opposed to par("usr")). I think that the following changes would be a nice addition: lines.polynomial

Hi, I can not comprehend the linear fitting results of polynoms. For example, given the following data (representing y = x^2): > x <- 1:3 > y <- c(1, 4, 9) performing a linear fit > f <- lm(y ~ poly(x, 2)) gives weird coefficients: > coefficients(f) (Intercept) poly(x, 2)1 poly(x, 2)2 4.6666667 5.6568542 0.8164966 However the fitted() result makes sense: >

Hello All First - a warning. I'm not very R or programming savvy. I am trying to do something without much luck, and have scoured help-pages, but nothing has come up. Here it is: I have a matrix (m) of approx 40,000 rows and 3 columns, filled with numbers. I would like to convert the contents of this matrix into another matrix (m_p), where the numbers of (m) have been coerced into a

Hi all, starting from a vector "v[1:n]" I would like to compute the coefficients of the polynomial (1+x^v[1])*(1+x^v[2])*...*(1+x^v[n]). The following code works but is extremely slow for a large "n" due to, I believe, the polynomial being factorized. I wanted to try the package "polynom" command "unclass" but I could not figure out how to input a

Hi all, I need to automate a process in order to prepare a a big loop in the future but I have a problem with the *command function* First I fit a model with lm > model1<-lm(data2[,2]~data2[,1]+I(data2[,1]^2)+I(data2[,1]^3)+I(data2[,1]^4)) I extract the coefficients to build the polynomial. coef<-as.matrix(model1$coefficients) In the next step I need to define the polynomial to

> Background: > OS: Linux Mandrake 9.1 > release: R 1.9.0 > editor: Xemacs 21.4 > frontend: ESS 5.1.23 > --------------------------------- > > Colleagues > Is there a function in R that is similar to polyval in matlab? (y = polyval(p,x) returns the value of a polynomial of degree n evaluated at x. The input argument p is a vector of length n+1 whose elements are the

When doing polynomial regression I believe it is a good idea to use the poly function to generate orthogonal polynomials. When doing this in Splus there is a handy function (transform.poly I think) to convert the coefficients produced by regression with the poly function back to the original scale. Has somebody written something similar for R ? Robert

Dear all - We perform some measurements with a machine that needs to be recalibrated. The best calibration we get with polynomial regression. The data might look like follows: > true_y <- c(1:50)*.8 > # the real values > m_y <- c((1:21)*1.1, 21.1, 22.2, 23.3 ,c(25:50)*.9)/0.3-5.2 > # the measured data > x <- c(1:50) > # and the x-axes > > # Now I do the following:

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?

If I do > example(lm) ... > mycoef <- function(object, ...) UseMethod("coef", object) > mycoef(lm.D9) Error in mycoef(lm.D9) : no applicable method for "coef" which is pretty surprising, as coef has a default method. After a bit of digging, this comes from do_usemethod having defenv = environment where the generic was defined */ defenv =

Dear all, Can any one tell me how can i perform Orthogonal Polynomial Regression parameter estimation in R? -------------------------------------------- Here is an "Orthogonal Polynomial" Regression problem collected from Draper, Smith(1981), page 269. Note that only value of alpha0 (intercept term) and signs of each estimate match with the result obtained from coef(orth.fit). What

Hello, I have 3 columns : a, b and a*b I would like to find the pair (a,b) so that a*b is the minimum but not from the points I measured but from the fit of the curve (I have more points that the ones given below but I fit only on this part because I know that the minimum a*b is in this interval). I thought doing it this way : - to fit a*b=f(a) abfit<-lm(ab ~ poly(a,8,raw=T)) - to use the

Merci beaucoup, Jean, for the bug report -- which I'm no "completeing" to R-bugs >>>>> "Jean" == Jean Coursol <coursol@cristal.math.u-psud.fr> >>>>> on Thu, 24 Jun 2004 15:22:37 +0200 (CEST) writes: Jean> I was exploring the polynom library with students: <and found a segmentation fault from parsing a long expression>

Hi. Is there an analog to abline() that can be used to plot a polynomial fit? For example, I can draw the straight-line fit fit <- lm(y ~ x) via abline(coef=fit$coef) but I'm not sure how to draw the polynomial fit fit <- lm(y ~ poly(x,2)) I do see the function curve(), but not how to prepare an expr for curve() based on the coefficients returned by the polynomial