similar to: Bug in poly() (PR#11243)

I am trying to use the marker method addlistener(). A simplified version of what I''m trying to do: var map; var marker; map = new mxn.Mapstraction(''myMap'',''google''); map.setCenterAndZoom(new mxn.LatLonPoint(45.559242,-122.636467), 15); marker = new mxn.Marker(new mxn.LatLonPoint(45.559242,

Dear R listers, I am regressing an ordered variable over an ordered independent variable using polr. The output lists every level of the ordered independent variable repeating its name and adding a suffix. In my case my variable is called "o.particip" and in my regression table I get the following: o.particip.L o.particip.Q o.particip.C o.particip^4 o.particip^5 o.particip^6 Is

Hi list, I have a real problem with plotting US state map. When I try to plot the northern state, there will be some blank space in the top of graph (see case 1 example), and when I plot southern states, there will be a blank space in the bottom of plot (see case 2). I spent almost 2 days to figure out a solution, but could not. Would you help me if you know what the problem is? Regards, Alireza

Does anyone know of a function that turns the coefficients of lm( y~ poly(x1 , x2, degree=2)) into something that can be interpreted easily. I was think along the lines of the matrix representation of quadratic forms: (x-mu)'A(x-mu) +k , and finding the eigenvectors/values of A, and the vector mu, but anything that allows me to visualise a contour plot would be great. Thanks Simon Bond

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 List, I am trying to do the following: 1. Use a BandPassFilter h[n] on a series x[n] 2. Then Decimate the series by a factor D such that y[k]=x[k*D] The decimation factor is considerable (10,000) so that filtering before the decimation, using convolve(), seems foolish. Can you think of an R implementation for a polyphase filter, that uses the fact that most samples will be thrown away...?

Hi Tobi, http://lab.llvm.org:8011/builders/perf-x86_64-penryn-O3-polly Looks like one of your boxes are bad and the other is good, but since they're both on the same bot, it looks to use as if it's unstable, spamming people every other build. :) Can you have a look, please? cheers, --renato

Full_Name: David Clifford Version: Version 1.5.1 (2002-06-17) OS: Red Hat 7.3 Submission from: (NULL) (128.135.149.55) For n values above 100 there appears to be a bug in contr.poly(n). The contrast matrix should have rank n-1. Running the code below gives output (ie errors) at n=98, 100 and every value greater than 102. for(n in 2:150) { K <- contr.poly(n) rnk <-

Full_Name: Jens Keienburg Version: 2.3.0 OS: Windows XP Submission from: (NULL) (193.174.53.122) I used the function lm() to calculate the coefficients of a polynome. If I used the function poly(t,2) to denote a polynome of form 1 + x + x^2, the coefficients are wrong. I appended an excerpt below: > t=1:100 > p=-20 - 10 * t + 2 * t^2 > p [1] -28 -32 -32 -28 -20 -8 8

The poly() function can create more variables than can be fitted when there are replicated values. In the example below, 'x' has only 5 distinct values, but I can apparently fit a 12th-degree polynomial with no error messages or even nonzero coefficients: R> x = rep(1:5,3) R> y = rnorm(15) R> lm(y ~ poly(x, 12)) Call: lm(formula = y ~ poly(x, 12)) Coefficients:

DDear developeRs, about a year ago, Alex Stolpovsky posted an issue with predict.lm on a fit generated using poly with the raw=TRUE option and too few new data (slightly modified reproducible example below). Alex did not get any reply. I have just stumbled on the same problem, and I think that this is a bug of function poly, which arises from the check whether the polynomial degree is

Dear R People: Suppose I want to estimate the parameters of the following AR model: (1 - phi_1 B - phi_2 B^2 - phi_9 B^9) x_t = a_t and I want to use the arima0 command from the ts library. How would I use the order subcommand, please? R Version 1.4.1 for Windows. Thanks! Sincerely, Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston -

Dear all, I am trying to transform polynomial coefficients from orthogonal form to the standard power basis. There's poly.transform in S-plus. Does anybody know how to do that in R ? I've found question about that in the archives of R-help but no real answer. Example : I'm doing polynomial regression of percentage of one insect in a community on altitude, precipitations,

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 r-help, I'm fitting a model with lm() and using the orthogonal polynomials from poly() as my basis: dat <- read.csv("ConsolidatedData.csv", header=TRUE) attach(dat) nrows <- 1925 Rad <- poly(Radius, 2) ntheta <- 14 Theta <- poly(T.Angle..deg., ntheta) nbeta <- 4 Beta <- poly(B.Beta..deg., nbeta) model.1 <- lm( Measurement ~ Block + Rad + Theta + Beta

I have a list of polygons generated by the contourLines() command (each object of the list is a list in itself with two objects: a vector of x values, and a vector of y values for each vertex). I wish to convert that list into a gpc.poly object of multiple contours. How do I do this? gpclib apparently has no method of coercing lists into the gpc.poly object type. As well, when I have a

Dear R experts, I am observing undesired behavior of predict(fit, newdata), in case when fit object is produced by lm() involving a poly(). Here is how to reproduce: x <- c(1:10) y <- sin(c(1:10)) fit <- lm(formula=y~poly(x, 5, raw=TRUE)) predict(fit, newdata=data.frame(x=c(1:10))) ## this works predict(fit, newdata=data.frame(x=c(1:1))) ## this is broken, error below Error in poly(x,

Dear UseRs, I just learnt that the number of columns of a data frame is not always what I thought it to be, and I wonder where I should have learnt about this. Consider the following example: dat <- data.frame(X1=1:10, X2=LETTERS[1:10]) ncol(dat) ## evaluates to 2 (of course) dat$X1poly <- poly(dat$X1,3) dat ## five columns displayed ncol(dat) ##

By any chance is anyone aware of an R function that duplicates Octave's poly function? Here is a description of Octave's poly function: Function File: poly (A) If A is a square N-by-N matrix, `poly (A)' is the row vector of the coefficients of `det (z * eye (N) - a)', the characteristic polynomial of A. As an example we can use this to find the eigenvalues

Dear r-devel list members, I've recently encountered the following problem using predict() with a model that has raw-polynomial terms. (Actually, I encountered the problem using model.frame(), but the source of the error is the same.) The problem is technical and concerns the design of poly(), which is why I'm sending this message to r-devel rather than r-help. To illustrate: