similar to: help with ols and contrast functions in Design library

Hi Muhammad From: "Muhammad Talha" <talha@worldcall.net.pk> To: "Asterisk Users Mailing List - Non-Commercial Discussion" <asterisk-users@lists.digium.com> Sent: Wednesday, December 22, 2004 2:07 PM Subject: Re: [Asterisk-Users] Zaphfc/BRI Configuration help > Thanks for lan for your reply can you share your extention.conf > setting . > >

Dear useRs I am looking for a way to randomise the values within a matrix: the conditions are that the sums of the rows and the sums of the columns should remain the same as in the original matrix. Any help would be appreciated Cheers Yann

I am playing with the a 1-way anova with and without the "-1" option. I have a simple cooked up example below but it behaves the same on a more complex real example. From what I can tell: 1) the estimated means of the different levels are correctly estimated either way (although reported as means with the -1 and as contrasts without the -1 as expected) 2) the residuals are

Hello, I would like to perform a multivariate regression analysis to model the relationship between m responses Y1, ... Ym and a single set of predictor variables X1, ..., Xr. Each response is assumed to follow its own regression model, and the error terms in each model can be correlated. Based on my readings of the R help archives and R documentation, the function lm() should be able to

Hi everybody, I'm trying to fit a Garch(1,1) process to the DAX returns. My data consists of about 2300 10day-logreturns in chronologically descending order (see attachment). But if I use the garch function I get a very high alpha_1 and a quite low beta, which doesn't make that much sense. I think I am missing something, but have no idea what it might be. I'd appreciate it a lot

Dear list members, I am trying to estimate parameters of the AR(1)-GARCH(1,1) model. I have one additional dummy variable for the AR(1) part. First I wanted to do it using garchFit function (everything would be then estimated in one step) however in the fGarch library I didn't find a way to include an additional variable. That would be the formula but, as said, I think it is impossible to add

Hi I have FC6 system in the office running SVN-trunk-r63567 It is behind a NAT router which I have configured to do port forwarding etc. Asterisk connects and registers correctly to my SIP service (Sipgate.co.uk) and I can make and receive calls from any SIP phone on the office LAN. The problem comes when I try to use a SIP phone at home (also behind a NAT router). The phone registers correctly

Hello. Consider the response-variable of data.frame df is constant, so analytically perfect fit of a linear model is expected. Fitting a regression line using lm result in residuals, slope and std.errors not exactly zero, which is acceptable in some way, but errorneous. But if you use summary.lm it shows inacceptable error propagation in the calculation of the t value and the corresponding

Hi all, I have a very easy questions (I hope). I had measure a property of plants, growing in three different substrates (A, B and C). The rest of the conditions remained constant. There was very high variation on the results. I want to do address, whether there is any difference in the response (my measurement) from substrate to substrate?

Petr, It works perfectly! But I still have a question; I have fit the following data; x,y,z 1,10,11 2,11,15 3,12,21 4,13,29 5,14,39 6,15,51 7,16,65 8,17,81 9,18,99 10,19,119 >dat.lm <- lm(z~I(x^2)+y, data=dat) >dat.lm Call: lm(formula = z ~ I(x^2) + y, data = dat) Coefficients: (Intercept) I(x^2) y 1.841e-14 1.000e+00 1.000e+00 How do I create the

Hi, I want to know what is there returned values of 'lm'. 'class' and 'lm' does not show that the returned value has the variable coefficients, etc. I am wondering what is the command to show the detailed information. If possible, I aslo want the lower level information. For example, I want to show that 'coefficients' is a named list and it has 2 elements.

Hi, I was lately debugging parts of my 'colAUC' function in caTools package, and in a process looked into other packages for calculating Areas Under ROC Curves (AUC). To my surprise I found at least 6 other functions: * wilcox.test * AUC from ROC package, * performance from ROCR package, * auROC from limma package, * ROC from Epi package, * roc.area from verification

Dear All, Thank you for the replies to my first thread here: http://r.789695.n4.nabble.com/global-optimisation-with-inequality-constraints-td3799258.html. So far the best result is achieved via a penalised objective function. This was suggested by someone on this list privately. I am still looking into some of the options mentioned in the original thread, but I have been advised that there may

Hi, I thought that 'coefficients' is a named list, but I can not refer to its element by something like r$coefficients$y. I used str() to check r. It says the following. Can somebody let me know what it means? ..- attr(*, "names")= chr [1:2] "(Intercept)" "y" $ Rscript lm.R > x=1:10 > y=1:10 > r=lm(x~y) > class(r) [1] "lm" >

Dear all, The following is a example that I run and hope to get a linear model. However, I find the lm() can not give correct coefficients for the linear model. I hope it's just my own mistake. Please help. TIA. Regards, Jinsong > x [1] 3.760216 3.997288 3.208872 3.985417 3.265704 3.497505 2.923540 3.193937 [9] 3.102787 3.419574 3.169374 2.928510 3.153821 3.100385 3.768770 3.610583

Dear All, I'm having a problem using functions in the gmodels library on an object of class mer from the lmer package. Code for a reproducible example is below. # Load lme4 library and sample data library(lme4) library(faraway) library(gmodels) data(penicillin) # Fit a linear mixed effects model fit4 <- lmer(yield ~ treat + (1|blend), penicillin) # Extract confidence intervals

In my post at https://stat.ethz.ch/pipermail/r-help/2011-October/292019.html I included an undefined term "ej". The problem code should be as follows. It seems like a simple linear programming problem, but for some reason my code is not finding the solution. obj <- c(rep(0,3),1) col1 <-c(1,0,0,1,0,0,1,-2.330078923,0) col2 <-c(0,1,0,0,1,0,1,-2.057855981,0) col3

Is there any way to maintain spaces, slashes, and parentheses in variable names when reading these into R? Of course, read.table converts these to periods. However, I know that it's not strictly illegal to have these characters in variable names as I am able to add them using the "variable editor" portion of the "data editor." I need to batch produce dozens of histograms

> On Mar 5, 2018, at 2:27 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > David: > > I believe your response on SO is incorrect. This is a standard OFAT (one factor at a time) design, so that assuming additivity (no interactions), the effects of drugA and drugB can be determined via the model you rejected: >> three groups, no drugA/no drugB, yes drugA/no drugB,

Dear R users, how can I extrapolate values listed in the summary of an lm model but not directly available between object values such as the the standard errors of the calculated parameters? for example I got a model: mod <- lm(Crd ~ 1 + Week, data=data) and its summary: > summary(mod) Call: lm(formula = Crd ~ 1 + Week, data = data, model = TRUE, y = TRUE) Residuals: Min