similar to: Scatter plot / LOESS, or LOWESS for more than one parameter

Hello, In the following I tried 3 versions of an example in R help. Only the two first predict command work. After : library(splines) require(stats) 1) fm1 <- lm(weight ~ bs(height, df = 5), data = women) ht1 <- seq(57, 73, len = 200) ph1 <- predict(fm1, data.frame(height=ht1)) # OK plot(women, xlab = "Height (in)", ylab = "Weight (lb)") lines(ht1, ph1) 2)

Hi, I've just installed libao-1.1.0 on a new Debian install. I also have alsa 1.0.27.1 installed. Debian is running under VirtualBox 4.2.12 under OSX 10.6.8, on a MacBookPro. libao does not work in stereo for the sampling rate of 44100, but it does for 8000, 11025, 22050and 48000. When I send it two channel output at a sampling rate of 44100, the result includes what sounds like skips,

Dear WizaRds, I tried to construct a two-phase sampling design in Survey just the way I hoped understood in Vienna - I was wrong. I think I am too stupid to create the correct subset for phase 2. Phase1: Sample 1000 parts with 80 defective. Phase2: Sample 100 parts out of these 1000 with 15 defective. 0:ok, 1:defunct. The table below gives the conditional sampling values. Please help me:

Hi I've 3 iax connections to my provider , each of them have own DID , PH1<----| | \/ PH2<-->|-----| <---------------------------> |----|<-- DID1 | A1 | <---------------------------> |ISP |<-- DID2 PH3<-->|-----| <---------------------------> |----|<-- DID3 I had iax phone on each of this connection , but now I want to terminate all

Hi, I have a data.frame with many variables for which I am performing the mean by subgroup, for a pair of variables at a time, where one of them for each pair defines the subgroup. The subgroups in the x$cm1 are 0, 1 and 2. x ph1 cm1 0.2345 2 1.2222 1 2.0033 0 0.0000 2 1.0033 1 0.2345 0 1.2222 2 2.0033 0 0.0000 1 1.0033 2 > meanbygroup <- as.vector(with(x, by(x$ph1, x$cm1, mean)))

I have a simple cdr configured with the default tables, here is a row of a good cdr report calldate | clid | src | dst | dcontext | channel | ect ..... ect .... 2008-08-29 10:16:49 | "C. BOUTON" <40> | 40 | XXXXXXXXXXX | phonesystems | SIP/40-08776938 | ect ..... ect .... I have replaced the number by

code: x <- rnorm(32) y <- rnorm(32) plot(x,y) lines(lowess(x,y),col='red') Now I need to sample the lowess function into matrix where one series will be X and other will be values of lowess at particular X. -- View this message in context: http://r.789695.n4.nabble.com/how-to-sample-lowess-loess-into-matrix-tp3053458p3053458.html Sent from the R help mailing list archive at

Hi Every Body, I don't know why some regression functions have no related prediction function. For example lowess, loess, lokerns, lpridge, lpepa, and ksmooth. What could help? Is there any global or wrapper function so that can help? Regards, Amir Safari --------------------------------- [[alternative HTML version deleted]]

Hi there, Just out of curious, is there any difference between loess() and lowess() in R (and Splus in fact). Which one is more often used? Thanks, Ko-Kang Wang ------------------------------------------------------------------------------ Ko-Kang Kevin Wang Statistical Analysis Division Leader Software Developers' Klub (SDK) University of Auckland New Zealand

Hi, I have a scatter plot of the variables GNI and Lifeexp (Gross National Income and Life Expectancy, both metric). So I plotted them and I want to add a regression line and a lowess line. I use lowess and not loess because I have missing values. My code: plot(GNI,Lifeexp) abline(lm(Lifeexp~GNI), col="red") y.loess<-loess(Lifeexp~GNI,na. action = na.exclude)

Hi Folks, I'm looking to do Confidence bands around LOESS smoothing curve. If found the older post about using the Standard error to approximate it https://stat.ethz.ch/pipermail/r-help/2008-August/170011.html Also found this one http://www.r-bloggers.com/sab-r-metrics-basics-of-loess-regression/ But they both seem to be approximations of confidence intervals and I was wonder if there was

I have a recurring graphics issue that I've not been able to resolve with R. If I make a series of regression estimates and then plot the estimated function for the regression lines over a scatter plot of the data, e.g., using a sequence of plot( ) and lines ( ) similar to those below

I know this is a dumb question but I'm pulling out what little hair I have left. I download the package and got the following: trying URL ' http://ftp.ussg.iu.edu/CRAN/bin/windows/contrib/2.14/Kendall_2.2.zip' Content type 'application/zip' length 52732 bytes (51 Kb) opened URL downloaded 51 Kb package ‘Kendall’ successfully unpacked and MD5 sums checked The downloaded

Hi, all, I want to use lowess(x, y) where x and y are vectors of length of 4000+. In fact, x and y are log of some vectors. So, some of the elements are NaN. lowess() can not take away those elements then do the fitting. It will give the error message and do nothing. 1. Can anybody tell me how to get rid of those NaN's and use lowess()? 2. How to get the LOWESS fitting values for any

Dear Masters, I'm driving crazy with the lowess() function.... my intent is smoothing confidence intervals for predicted y values in a linear model lm() setting since in the predict() function there exists an option for predicting NA values, I instead encounter problems when I fit a missing values x variable to the predicted terms.....,impossible task!!! I've been banging on my head

Dear all, please do you have any recommendation about a more advanced function in R for lowess/loess regression ? the basics lowess() or loess() do not perform as well as I would expect. thanks very much, Bogdan [[alternative HTML version deleted]]

I have an NT4 server as PDC for a domain: WG. Domain members (on 3 subnets) can either log into the domain, or at least access shares from the network neighboorhood if they don't want to log on. When I boot a samba server as a workgroup member (I don't log it into the domain) everything runs fine for about 24 hours; domain or WG members can access shares on any machine including the

As I've mentioned a number of times. I find it very useful to have lowess() become a generic function so that a lowess.formula() can be defined. Below is a patch that makes both changes, as well as updating the corresponding help documentation. Gregory R. Warnes Manager, Non-Clinical Statistics Pfizer Global Research and Development Tel: 860-715-3536 ? DESCRIPTION ? Makefile ?

Colleagues ---------------------------------- System info: R version rw1022 on NT ESS v. 5.1.18 using emacs ver. 20.4 ---------------------------------- I would like to access the residuals from a lowess fit (function lowess() ) as an aid to assessing whether I am over-smoothing or under-smoothing a dataset (as in Cleveland's book "Visualizing data", section 3.3) Unless I

Hello Masters, I run the loess() function to obtain local weighted regressions, given lowess() can't handle NAs, but I don't improve significantly my situation......, actually loess() performance leave me much puzzled.... I attach my easy experiment below #------SCRIPT---------------------------------------------- #I explore the functionalities of lowess() & loess() #because I have