similar to: Problem plotting with xyplot

Hi there, I would like to draw a scatter plot and fit a smooth line by loess. Below is the data. However, the curve line started from 0, which my "resid" list doesn't consist of 0 value. It returned some warnings which I don't know if this is the reason affecting such problem. Here I also attached the warning messages. Please let me know if there is a solution to fix this. Thank

Hi all, I'm trying to find a way to get xyplot to produce a second set of axes outside the right hand side of the graph. This is my progress so far: EE <- equal.count(ethanol$E, number=9, overlap=1/4) xyplot(NOx ~ C | EE, data = ethanol, prepanel = function(x, y) prepanel.loess(x, y, span = 1), xlab = "Compression Ratio", ylab = "NOx (micrograms/J)",

xyplot doesn't seem to want to label my x-axis with dates but instead puts the day-number for each date. begdate is the number of days since January 1, 1960 and was initially created by library(date) ... polls$begdate<-mdy.date(begmm,begdd,begyy) I create a new dataframe (pollstack) which includes begdate. In the process begdate seems to lose its date attribute so I redo it as: >

I'm updating the loess routines to allow for, among other things, arbitrary local polynomial degree and number of predictors. For now, I've given the updated package its own namespace. The trouble is, panel.loess still calls the original code in package:stats instead of the new loess package, regardless of whether package:loess or package:lattice comes first in the search list. If I

I ran the following script from xyplot Examples using Tin-R on Windows and saw no plot produced. EE <- equal.count(ethanol$E, number=9, overlap=1/4) xyplot(NOx ~ C | EE, data=ethanol, prepanel = function(x,y) prepanel.loess(x, y, span=1), xlab="Compression Ratio", ylab="NOx (micrograms/J)", panel = function(x,y) { panel.grid()(h = -1, v=2)

Dear all; I wish to create a graphic object combing an xyplot() and an mtext(). My code looks like following, gmv <- { trellis.device("windows", bg="white", width = 7, height = 7) xyplot(Mvol ~ Age | Nl * Th , data = Hft1, prepanel = function(x, y) prepanel.loess(x, y, span = 1), xlab =list(label = "Age (Years)", font = 2),

Respected R experts, I am trying to apply a user function that basically calls and applies the R loess function from stat package over each time series. I have a large matrix of size 21 X 9000000 and I need to apply the loess for each column and hence I have implemented this separate user function that applies loess over each column and I am calling this function foo as follows:

Hi: (Tried to find a bug report about this issue, but was unable to find it, let me know if this is a known issue) I have been working on an interface to highlight xyplot panels on mouse overs in JavaGD but I have stumbled with what seems to be a bug in trellis.focus. I am using R 2.8 with lattice 0.17-15 *** To replicate the bug: 1.- display an xyplot. For example, from the xyplot help page:

Hello, I found a little BUG in loess <stats>. It does not receive the iterations parameter. It can be debugged in the following way: THIS IS AN EXCERPT FROM THE CODE: .... fit <- simpleLoess(y, x, w, span, degree, parametric, drop.square, normalize, control$statistics, control$surface, control$cell, iterations, control$trace.hat) Replace argument iterations with

Dear R-users, By default, the xyplot function automatically defines the axis ranges based upon the content of y and x variables. However, when one includes some calls to other panel.<something> functions in the panel argument, the results might be out of range and not show up in the final graphs (see lower ends of the loess line in the following example). Is there a way one can capture the

Hi mailinglist members, I’m actually working on a time series prediction and my current approach is to decompose the series first into a trend, a seasonal component and a remainder. Therefore I’m using the stl() function. But I’m wondering how to get the single components in order to predict the particular fitted series’. This code snippet illustrates my problem: series <-

Dear R experts, I have a problem that is a related to the question raised in this earlier post https://stat.ethz.ch/pipermail/r-help/2007-January/124064.html My situation is different in that I have only 2 predictors (coordinates x,y) for local regression but a number of global ("parametric") offsets that I need to consider. Essentially, I have a spatial distortion overlaid over a

Hi all, I am doing a projection pursuit regression using the ppr() function from modreg. I would also like to use predict.ppr(). However, I cannot find any information about it in the help files. There is a link to predict.ppr in the index for modreg, but that link is to the help for ppr(). Has predict.ppr() not been implemented? If not, does anyone have a suggestion as to how to implement

Hi, I met a probem recently and need your help. I would really appreciate it. I kept receiving the following error message when running a program: 'Error in svd(X) : infinite or missing values in x'. However, I did not use any svd function in this program though I did include the function pseudoinverse. Is the problem caused by doing pseudoinverse? Best regards, Tongtong

Dear List, Having had my appetite sufficiently whetted by Prof. Ripley's email about the new graphics capabilities in Unixes, I wanted to try them out. I updated to svn r44608, configured with the following options: R is now configured for x86_64-unknown-linux-gnu Source directory: .. Installation directory: /usr/local C compiler: gcc -O3 -g -std=gnu99

Hi, All, I have a dataset with binary response ( 0 and 1) and some numerical covariates. I know I can use logistic regression to fit the data. But I want to consider more locally. So I am wondering how can I fit the data with 'loess' function in R? And what will be the response: 0/1 or the probability in either group like in logistic regression? Thank you, Cindy [[alternative HTML

hi! i want to change the "robustness weights" used by loess. these are described on page 316 of chambers and hastie's "statistical models in S" book as r_i = B(e_i,6m) where B is tukey's biweight function, e_i are the residulas, and m is the median average distance from 0 of the residuals. i want to change 6m to, say, 3m. is there a way to do this? i cant

Hi, I have a data frame with 6563 observations. I can run a regression with loess using four explanatory variables. If I add a fifth, R crashes. There are no missings in the data, and if I run a regression with any four of the five explanatory variables, it works. Its only when I go from four to five that it crashes. This leads me to believe that it is not an obvious problem with the data,

I noticed a problem using R 2.7.1 on Windows XP SP2 with the precompiled Atlas Rblas.dll. Running the code below causes R to crash. I started R using Rgui --vanilla and am using the precompiled Atlas Rblas.dll from cran.fhcrc.org dated 17-Jul-2007 05:04 for Core2 Duo. The code that causes the crash: x <- rnorm(100) y <- rnorm(100) z <- rnorm(100) loess(z ~ x * y) loess(z ~ x) does

Hi, I'd like to plot 4 groups of data using xyplot and panel.superpose so that the points are overlayed on a single plot. For each group of data I'd also like a loess smoothed function (using panel.loess). I have tried the following: xyplot(series ~ time | gr, data=etable, panel = function(x,y, ...) { panel.superpose(x,y, ...) panel.loess(x,y,span=.15)