similar to: Plotting polynomial fit

(I'm reposting this message because the original has not appeared after about 2 days. Sorry if it shows up twice.) Hello. First, thanks to those who responded to my recent inquiry about using contour() over arbitrary (x,y) by mentioning the interp() function in the akima package. That worked nicely. Now for a new question: I would like to use a pair of prediction intervals to

Hello. I have an R program that calls gawk (GNU Awk 3.06 for Windows) from within pipe() to preprocess a large file before it is read into a data frame with read.table(). I've recently upgraded from Win98SE to WinXP, and have also upgraded from R1.5.0 to R1.6.1 over the past month or so. This program worked before the upgrade(s), but now fails. I observe the following sort of behavior with

Hi. The following statement works fine in R-win 1.8.0, but yields a syntax error in R-win 2.0.1 (and possibly in other versions after 1.8.0): plot(c(1,2),main=expression(a==b==c)) I note that the following workaround executes successfully in both versions of R... plot(c(1,2),main=expression(a*"="*b*"="*c)) ...but I don't really understand

Full_Name: Ronnen Levinson Version: 1.5.1 OS: Mac OS 10.1 Submission from: (NULL) (12.232.201.92) The value returned by strptime behaves badly after arithmetic operation and/or combination. > a=strptime("2002-06-01 12:15:01","%Y-%m-%d %H:%M:%S") > a [1] "2002-06-01 12:15:01" > a+0 [1] "1932-04-25 21:46:45" > a+3600 [1] "1932-04-25

Hi. Can anyone suggest a simple way to obtain in R a list of vector coordinates of the following form? The code below is Mathematica. In[5]:= Flatten[Table[{i,j,k},{i,3},{j,4},{k,5}], 2] Out[5]= {{1,1,1},{1,1,2},{1,1,3},{1,1,4},{1,1,5},{1,2,1},{1,2,2},{1,2,3},{1 ,2,4},{1,2, 5},{1,3,1},{1,3,2},{1,3,3},{1,3,4},{1,3,5},{1,4,1},{1,4,2},{1,4,3}, {1,4,

Hello. Is it possible to set specify the font used by legend()? I would like to specify a fixed-width font so that I can line up parts of vertically stacked curve labels. For example, it would be nice if I could align the names, ages, and weights in the following three curve labels: Bob age=7 weight=100 Alexander age=13 weight=150 Susan age=20 weight=130 Is there perhaps a clever

Hi. As shown in the simplified example below, I'm having trouble allocating memory for large vectors, even though it would appear that there is more than enough memory available. That is, even with a memory limit of 1500 MB, R 2.6.1 (Win) will allocate memory for a first vector of 285 MB, but not for a second vector of the same size. Forcing garbage collection does not seem

Hey all, first time poster here. I'm new to R and working on my first real programming and forecasting asignment. I'm using unemployment data from 1948-2012. I successfully completed part a and the linear fit for part b, but i am really struggling fitting a polynomial with a power greater than 2 to my forecast. I'll upload my R code at the bottom. Any help is very much appreciated!

Hello. I have an XYY series that I would like to graph with matplot() or some other single function that will do the trick. The X in question is a vector of POSIXt values obtained from strptime(). Is it possible to tell matplot() how to handle POSIXt x values? I have examined the examples at http://lark.cc.ukans.edu/~pauljohn/R/statsRus.html#5.22 , but would prefer not have to overlay the

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 <-

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 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 All, This might seem elementary to everyone, but please bear with me. I've just spent some time fitting poly functions to time series data in R using lm() and predict(). I want to analyze the functions once I've fit them to the various data I'm studying. However, after pulling the first function into Octave (just by plotting the polynomial function using fplot() over

I wonder how one in R can fit a 3rd degree polynomial to some data? Say the data is: y <- c(15.51, 12.44, 31.5, 21.5, 17.89, 27.09, 15.02, 13.43, 18.18, 11.32) x <- seq(3.75, 6, 0.25) And resulting degrees of polynomial are: 5.8007 -91.6339 472.1726 -774.2584 THanks in advance! -- Jonas Malmros Stockholm University Stockholm, Sweden

Hello. Is there an easy-to-use contour plot function analogous to scatterplot3d that can draw handle a dataset of arbitrary (x,y,z) triplets? That is, say x, y, and z are each measured quanties, and exhibit neither order nor regularity. I looked at the lattice package function "contourplot" but it seems complicated, and it's not clear from the documentation whether it can

Suppose you have a vector of data in x and response values in y. How do you plot together both the points (x,y) and the curve that results from the fitted model, if the model is not y ~ x, but a higher order polynomial, e.g. y~poly(x,2)? (In other words, abline doesn't work for this case.) Thanks, --Paul -- Paul Lynch Aquilent, Inc. National Library of Medicine (Contractor)

Hi. I often wind up with many help windows cluttering my RGui screen when running Windows R 2.0.1. Is there an R instruction to close one or more help windows, or an RGui command to close all help windows? Yours truly, /Ronnen. /P.S. E-mailed CC:s of posted replies appreciated. [[alternative HTML version deleted]]

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 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

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