similar to: Linear Regression with slope equals 0

HOwdy I read R books about scale function for variable transformation. Acoording to this book scale function leads me to better regression results. Or am I worng? I hope somebody tell me about a scale function? Is it for variable transformation? -- Kum-Hoe Hwang, Phone : 82-31-250-3516Email : phdhwang@gmail.com [[alternative HTML version deleted]]

Hello guys, I am a total newbie on R, having downloaded it, read the documentation and started playing with it right now. My general question is what 'lr' model can be used for doing a linear regression on points that have a variance associated with them (ie. Monte Carlo simulation results). Actually my Data sets look like: Timestep Energy Variance_of_the_Energy 0.0005 -14.876840

Hi! Consider this code. setClass("Ctest" ,representation( test="character" ,bla="character" ,mod="lm" ) ) new("Ctest",test="bla") #This produces an error. #Error in validObject(.Object) : Invalid "Ctest" object: Invalid object for slot "mod" in class "Ctest": got class

Hello, I've written a simple (although probably overly roundabout) function to test whether two regression slope coefficients from two linear models on independent data sets are significantly different. I'm a bit concerned, because when I test it on simulated data with different sample sizes and variances, the function seems to be extremely sensitive both of these. I am wondering if

Hi I have (8 measures * 96 groups) = 768 datasets for which I did linear regressions using lm(). Now I want to compare the slopes for each of the 8 measures in each of the 96 groups. As I understand , I can not use > anova(lm1, ..., lm8) as the lm1 ... lm8 are based on different datasets. I also read in previous discussions in this list, that I can see if the slope +- stddev(slope)

Hello to the whole group. I am a newbie to R, but I got my way through and think it is a lot easier to handle than other software packages (far less clicks necessary). However, I have a problem with respect to the summary of regression results. The summary function gives sth like: Residuals: Min 1Q Median 3Q Max -0.46743 -0.09772 0.01810 0.11175 0.42252

Hi all, I am trying to bootstrap a small data set into 1000 "pseudodatasets" and then run an ANOVA on each one. Can anyone provide guidance on how I could do this? Thank you. -Dan Janes ************************************************ Dan Janes, Ph.D. Harvard University/OEB 26 Oxford St. Cambridge, MA 02138 Office: 617-496-2375 Fax: 617-495-5667 Email: djanes at oeb.harvard.edu

I'm running Samba 3.0.0 and seeing a lot of Oct 20 10:02:25 littleboy smbd[2062]: [2003/10/20 10:02:25, 0] lib/util_str.c:safe_strcpy_fn(577) Oct 20 10:02:25 littleboy smbd[2062]: ERROR: NULL dest in safe_strcpy messages. Most things (except the problem I posted earlier) seem to work perfectly.

I am learning ggplot2, and need your help. When I try > p <- ggplot(mtcars, aes(x = wt, y=mpg)) + geom_point() > p + geom_abline(slope=5) (from http://had.co.nz/ggplot2/geom_abline.html) the slope of the abline does not change, but this works: > p + geom_abline(intercept=20) In order to have slope work, I have to use > p + geom_abline(aes(slope=5)) Is it a bug, or is there

Dear forum members, How can I force a negative slope in a linear regression even though the slope might be positive? I will need it for the purpose of determining the trend due reasons other than biological because the biological (genetic) trend is not positive for these data. Thanks. Julia Example of the data: [1] 1.254 1.235 1.261 0.952 1.202 1.152 0.801 0.424 0.330 0.251 0.229

To all I have some simple questions pertaining to weights used in regression. If the variability of the dependent variable (y) is a function of the magnitude of predictor variable (x), can the use of weights give an appropriate answer to the regression parameters and the std errors? Assume that y at x=1 and 6 has a standard deviation of 0.1 and at x=11 it is 0.4 Then according to a web page on

Dear R-Users, I am new to R, so please excuse the ignorance. I have data: x (2.14, 2.41, 1.09, 0.17, 8.18) y (3.81, 5.13, 0.63, 0.75, 6.35) I would like to use simple linear regression and test 2 things: 1) slope of line of best fit is statistically different from 1 2) y-intercept is statically different from 0 Could anyone provide me with the R terminology to do this? Thanks so much, Dan

Hi, Is there a neat way of working out the slope of a flat surface in R? Given (x,y,z) co-ordinates of the four corners of a square, is there a function which will allow me to calculate the "mean" slope of the surface in a given direction? Thanks in advance.. Laura Laura Quinn Institute of Atmospheric Science School of Earth and Environment University of Leeds Leeds LS2 9JT tel: +44

Is there a way to do a linear regression with lm (having one predictor variable) and constrain the slope of the line to equal 1? Tom -- View this message in context: http://www.nabble.com/Linear-Regression-with-lm-Forcing-the-Slope-to-Equal-1-tf4828804.html#a13815432 Sent from the R help mailing list archive at Nabble.com.

Hello, I have a challenge! I have a large dataset with three columns, "date","temp", "location". "date" is in the format %m/%d/%y %H:%M, with a "temp" recorded every 10 minutes. These temperatures of surface temperatures and so fluctuate during the day, heating up and then cooling down, so the data is a series of peaks and troughs. I would like

Dear All, First of all I would like to say I do not have much knowledge about this subject, so most of you can find it really easy. I am doing a linear regression and I want to test if the slope of the curve is 0. R gives the summary statistics: Call: lm(formula = x ~ s) Residuals: Min 1Q Median 3Q Max -0.025096 -0.020316 -0.001203 0.011658 0.044970 Coefficients:

Hello, I have a linear model with different slopes for different treatment groups. I need to pairwise compare the different slope estimates for the different treatment groups. Is there a package that does pairwise comparisons of slope coefficients, making the appropriate adjustments in the P values? Thanks, John. -- ========================================== John Janmaat Department of

Is there an easy way to do a linear model with an a priori known slope? In essence, I want to minimize the residuals around a line of known slope. -R -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

I want to fit a linear model with fixed slope e.g. y = x + b (instead of general: y = a*x + b) Is it possible to do with lm()? Regards, Ryszard -------------------------------------------------------------------------- Confidentiality Notice: This message is private and may ...{{dropped:11}}

Hi for some data I working on I am merely plotting time against temperature for a variable named filmclip. So for example, I have volunteers who watched various film clips and have used infared camera to monitor the temperature on their face at every second of the clip. The variable names I have used are Normalised ( for the temperature) and Frame (for the time in seconds). So I have fitted a