similar to: polynomial expansion in R

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

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

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

Hi: I have some problems when I use the function "solve" function in a loop. In the following code, I have a diagonal martix "ttt" whose elements change in every iteration in a loop. I defined a "dpoMatrix"class before the loop so I do not need to define this class every time in the loop. The reason is to save some computing time. The code is below. The inverse

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 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

Does anybody know if there is a built in fuction to use create polynomial distributed lags (sometimed called Almon lag) on linear models? Thanks Francisco _________________________________________________________________ See when your friends are online with MSN Messenger 6.0. Download it now

Hi: I used the function "lme" in R and Splus-7. With the same dataset and same argument for the function, I got quite different estimation results from these two software. Anyone has this experience before? zhong --------------------------------- Get your own web address. [[alternative HTML version deleted]]

Hi: Is there any function in R which can convert the long/lat to UTM(Universal Transverse Mercator)? There are quite a few converters on Internet. However, the interface is designed as input->output which I can not convert lots of locations at the same time. Another question is whether there is a function in R which can tell the time zone from the location's lat/long? Thank you!

I am trying to understand what is the difference between linear and polynomial kernel: linear: u'*v polynomial: (gamma*u'*v + coef0)^degree It would seem that polynomial kernel with gamma = 1; coef0 = 0 and degree = 1 should be identical to linear kernel, however it gives me significantly different results for very simple data set, with linear kernel

Hi everybody! I'm looking some way to do in R a polynomial fit, say like polyfit function of Octave/MATLAB. For who don't know, c = polyfit(x,y,m) finds the coefficients of a polynomial p(x) of degree m that fits the data, p(x[i]) to y[i], in a least squares sense. The result c is a vector of length m+1 containing the polynomial coefficients in descending powers: p(x) = c[1]*x^n +

Hello, i'm fairly familiar with R and use it every now and then for math related tasks. I have a simple non polynomial function that i would like to approximate with a polynomial. I already looked into poly, but was unable to understand what to do with it. So my problem is this. I can generate virtually any number of datapoints and would like to find the coeffs a1, a2, ... up to a given

Hi: I am doing a MCMC algorithm which is well known to consume much computer memory. And I have a problem everytime I run my R program. It stopped at certain iteration and says "can not allocate a vector of 19 kb". It seems that the computer's memory has been exhausted. However, it is said that after each iteration the objects (such as a huge matrix) can be set to NULL. And the

Hi: I have two time series y(t) and x(t). I want to regress Y on X. Because Y is a time series and may have autocorrelation such as AR(p), so it is not efficient to use OLS directly. The model I am trying to fit is like Y(t)=beta0+beta1*X(t)+rho*Y(t-1)+e(t) e(t) is iid normal random error. Anybody know whether there is a function in R can fit such models? The function can also let me specify

Hey all, I'm performing polynomial regression. I'm simulating x values using runif() and y values using a deterministic function of x and rnorm(). When I perform polynomial regression like this: fit_poly <- lm(y ~ poly(x,11,raw = TRUE)) I get some NA coefficients. I think this is due to the high correlation between say x and x^2 if x is distributed uniformly on the unit interval

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 <-

Hi, I want to plot a polynomial in the form like ax^2 + bxy + cy^2 + dx + ey + f =0 without solving it(since I may have 3 or 4 dimensional polynomial and it's really hard to solve). Is there any way to plot this kind of polynomial? Thanks a lot! -- View this message in context: http://www.nabble.com/Plot-2-d-Polynomial-without-solving-it-tp24331313p24331313.html Sent from the R help

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 have a polynomial (a big one) and I would like to find a root of it between [-inf, -3] (it's known there is one root in this interval)... How to find that root? In using "uniroot" I need to supply the bounds.... In using "polyroot" I need to write it in the strict sens polynomial format... but I cannot... i.e. the polynomial is implicit... Thank you!

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