similar to: (v2) quadratic trends and changes in slopes (R-help digest, Vol 1 #52 - 16 msgs)

-----Original Message----- Message: 6 Date: Mon, 20 Jan 2003 01:11:24 +0100 From: Martin Michlmayr <tbm at cyrius.com> To: r-help at stat.math.ethz.ch Subject: [R] quadratic trends and changes in slopes I'd like to use linear and quadratic trend analysis in order to find out a change in slope. Basically, I need to solve a similar problem as discussed in

I'd like to use linear and quadratic trend analysis in order to find out a change in slope. Basically, I need to solve a similar problem as discussed in http://www.gseis.ucla.edu/courses/ed230bc1/cnotes4/trend1.html My subjects have counted dots: one dot, two dots, etc. up to 9 dots. The reaction time increases with increasing dots. The theory is that 1 up to 3 or 4 points can be counted

Hi all, I've just installed 1.9.18p5 (although I've just got the mail about 1.9.18p6, so I'll be putting that on now) and am having a problem with browsing... [samba@suau1] ~> smbclient -L suau1 Added interface ip=134.225.16.5 bcast=134.225.19.255 nmask=255.255.252.0 Server time is Mon May 11 15:24:39 1998 Timezone is UTC+1.0 Password: Domain=[UNSEEN] OS=[Unix]

I'm experiencing similar problems with a 3C996-T under 4.8-REL. In particular, connecting a 4.8-REL machine to a 5.1-REL machine leads to some interesting situations: I can do simple pings across the link, but ssh fails, and heavy pings crash the 4.8 machine. Similarly changing the interface configuration with ifconfig tends to crash the 4.8 machine (mtu, link0, up/down, etc). The

Hello. I have some further problems with modelling an optimization problem in R: How can I model some optimization problem in R with a linear objective function with subject to some nonlinear constraints? I would like to use "optim" or "constrOptim", maybe with respect to methods like "Simulated Annealing" or "Sequential Quadric Programming" or something

Hello. I have some problems, when I try to model an optimization problem with some constraints. The original problem cannot be solved analytically, so I have to use routines like "Simulated Annealing" or "Sequential Quadric Programming". But to see how all this works in R, I would like to start with some simple problem to get to know the basics: The Problem: min f(x1,x2)=

I am having difficulty getting the trend.spatial function in geoR to work properly. After creating a trend.spatial object with a covariate, I try to add the command into my likfit() function as follows: trend1.trend.spatial <- trend.spatial("1st", trend1.geodata) trend1.spatial.EC0.1.reml <- likfit(spatial.geodata, trend1.trend.spatial, ini.cov.pars = spatial.EC0.1.eyefit,

Hi All, I am a newcomer to R. Could anyone explain me how to define link functions for either mu/sigma to allow for quadratic trends in the same, when fitting non-stationary GEV distributions? Thanks -- View this message in context: http://www.nabble.com/QUADRATIC-TREND-FOR-LINK-FUNCTIONS-ON-NON-STATIONARY-GEV-tp23360751p23360751.html Sent from the R help mailing list archive at Nabble.com.

Dear list users How is it possible to visualise both a linear trend line and a quadratic trend line on a plot of two variables? Here my almost working exsample. data(Duncan) attach(Duncan) plot(prestige ~ income) abline(lm(prestige ~ income), col=2, lwd=2) Now I would like to add yet another trend line, but this time a quadratic one. So I have two trend lines. One linear trend line

Hello, I want to know if two quadratic regressions are significantly different. I was advised to make the test using step 1 bootstrapping both quadratic regressions and get their slope coefficients. (Let's call the slope coefficient *â*^1 and *â*^2) step 2 use the slope difference *â*^1-*â*^2 and bootstrap the slope coefficent step 3 find out the sampling distribution above and

I have two vectors: both have possible values of 1,-1, or 0 trend1 <- c(1,1,1,1,1,1,-1,-1,-1,-1,-1,-1) trend2 <- c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,) i want to create a third vector that is conditional upon these two vectors: if (trend2 == 1 && trend1 == 1) {position <- 1} elseif (trend2 == -1 && trend1== -1) {position <- 1} else {position <- 0} based on this two

Hello, There is a task to derive a linear trend, for ex. 5 units/month for values located at the georeferenced global latidute-longitude grid. There are several grids corresponding to time steps, say for a month with 6 hour interval. Sure, one can create a loop and derive a trend value for each data point. Is there a better practice for this task to express it in a line or two or a dedicated

Dear List, First off, this is completely off topic, but I thought others might find it interesting. The good people at IBM are apparently providing written interpretations of results now. I was working with a student the other day with simple nonparametric tests using SPSS, and under the nonparametric test tab, it defaulted to something like "Let SPSS decide which test to use". Even

Hi all see $subj http://www.google.com/trends?q=llvm congrats! P.S. sorry if known. best regards -- Valery A.Khamenya -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20080318/2bfc6887/attachment.html>

Google trends will display results for pretty much any query you can think of On Mon, Mar 17, 2008 at 7:16 PM, Valery Khamenya <khamenya at gmail.com> wrote: > Hi all > > see $subj > > http://www.google.com/trends?q=llvm > > congrats! > > P.S. sorry if known. > > best regards > -- > Valery A.Khamenya > _______________________________________________

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Odhiambo Washington <odhiambo at gmail.com> wrote: > Traceback (most recent call last): > File "./main.py", line 304, in <module> > message_infos = GetMessageInfos(opts) > File "./main.py", line 104, in GetMessageInfos > for mailbox in m.GetMailboxes(): > File "/scripts/mail-trends/mail.py", line 61, in GetMailboxes >

I have data on every grade in all elementary schools in Chicago over 5 years. I would like to estimate a trend over time for each grade in each school. There are 17,600 data all together (about 460 schools, nearly 8 grades each, over 5 years). Is there a not-so-hard way to do this in R (I was thinking of using rlm)? ______________________________________________________________________ Stuart

Dear All, I am given some noisy data which (by naked eye) appears to be oscillating first but finally growing. Is there any statistical set (I mean something different from e.g. a linear fit, which would not be convincing at all in my case) to detect growth (possibly without relying on any data fitting)? Many thanks Lorenzo

Hi all, I am using GAM to model time trends in a logistic regression. Yet I would like to extract the the fitted spline from it to add it to another model, that cannot be fitted in GAM or GAMM. Thus I have 2 questions: 1) How can I fit a smoother over time so that I force one knot to be at a particular location while letting the model to find the other knots? 2) how can I extract the matrix