similar to: Outline For Asterisk Book - Please Review & Comment

Hello all, I've been invited to do a presentation on Asterisk for the Ohio Linuxfest in Columbus this weekend (http://www.ohiolinux.org). Rough estimates are that nearly 500 people will be attending. I've been working on an outline for a couple of weeks and I would like to have some peer review of the information presented. I am going to have to cut down the content to make it fit in

Dear R Help, I have a set of data of heights of trees described by area that they are in. The areas are numerical (0 to 7). ht area 1 320 3 2 410 4 3 230 2 4 360 3 5 126 1 6 280 2 7 260 2 8 280 2 9 280 2 10 260 2 ....... 180 450 4 181 90 1 182 120 1 183 440 4 184 210 2 185 330 3 186 210 2 187 100 1 188 0 0 I want to convert the

All, I'm needing volunteers to help moderate the sessions of the LLVM Developers' Meeting. All you need to do is introduce the speaker, make sure the speaker stays on time, and run Q&A at the end (run a microphone, select people, etc). Its a pretty easy job, but critical for our meeting to run smoothly. If you are interested in moderating, please send me your top 2 session choices.

Dear R People: I'm using R2HTML but having a strange result. Here is the original data: resp trt block 90.3 A I 89.2 A II 98.2 A III 93.9 A IV 87.4 A V 97.9 A VI 92.5 B I 89.5 B II 90.6 B III 94.7 B IV 87.0 B V 95.8 B VI 85.5 C I 90.8 C II 89.6 C III 86.2 C IV 88.0 C V 93.4 C VI 82.5 D I 89.5 D II 85.6 D III 87.4 D IV 78.9 D V 90.7 D VI And here are the commands: > resin1.df <-

I am wondering how to interpret the parameter estimates that lm() reports in this sort of situation: y = round(rnorm(n=24,mean=5,sd=2),2) A = gl(3,2,24,labels=c("one","two","three")) B = gl(4,6,24,labels=c("i","ii","iii","iv")) # Make both observations for A=1, B=4 missing y[19] = NA y[20] = NA data.frame(y,A,B) nonadd = lm(y ~

Dear R users, I'm a bit perplexed with the effect sort has here, as it is different on Windows vs. linux. It makes my factor levels and subsequent plots different on the two systems. Given: types <- c("PC-D-Euro-0", "PC-D-Euro-1", "PC-D-Euro-2", "PC-D-Euro-3", "PC-D-Euro-4", "PC-D-Euro-5", "PC-D-Euro-6",

Hi, I have a 2D chart that is divided into four quadrants, I, II, III, IV: plot(1:10,ylim=c(0,10),xlim=c(0,10),type="n") abline(v=5,h=5) text(x=c(7.5,7.5,2.5,2.5),y=c(2.5,7.5,7.5,2.5),labels=c("I","II","III","IV")) I would like to fill each quadrant with a background color unique to the quadrant. Does anyone know how to do this in R? Thanks, --

Dear LLVM users, The development of LLVM has been supported primarily by funding from the National Science Foundation and the University of Illinois. in order to maintain our sources of funding and attract new ones, It is important for us to be able to document how LLVM is benefiting companies, universities, other organizations, and individuals in the outside world. (The information

R-help, I have a data frame with one column containing roman numbers The data are not sorted as : I II III IV V VI VII VIII IX X XI XII XIII XIV XV Using data[order(data$Roman),] does not do the job. How can this be done? Thanks in advance.

Hi, I was wondering why anova() and drop1() give different tail probabilities for F tests. I guess overdispersion is calculated differently in the following example, but why? Thanks for any advice, Tom For example: > x<-c(2,3,4,5,6) > y<-c(0,1,0,0,1) > b1<-glm(y~x,binomial) > b2<-glm(y~1,binomial) > drop1(b1,test="F") Single term deletions Model: y ~

I have two ideas about it. 1- i) Entering variables in quadratic form is done with the command I (variable ^ 2) - plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = "LOO" You could also use a new variable NIR_sq <- (NIR) ^ 2 ii) To insert a square variable, use syntax I (x ^ 2) - it is very important to insert I before the parentheses. iii) If you want to

Hello All, I am new to R, and I am writing to seek your advice on how best to use it to run R's various normality tests in an automated way. In a nutshell, my situation is as follows. I work in an investment bank, and my team and I are concerned that the assumption we make in our models that the returns of assets are normally distributed may not be justified for certain asset classes. We are

I'm experiencing some confusion with the ellipsis argument (...). In my .Rprofile, I have the following functions: stderr <- function(x, ...) { sqrt( var(x, ...) / length(x) ) } se <- stderr I can use tapply to calculate some means: > tapply( Diameter, factor(Region), mean, na.rm=TRUE ) I II III IV V 0.02896429

Many thanks, My goal is to make a plott like attached but the Y axis starts in XIV and end at top in I. Generally for instance in excel X axis is categories but Y axis is numbers I want the contrary plotted in lines, your last help is near what I look but barplot is not needed. Hope you can help me thanks in advance. 2018-05-22 0:58 GMT+02:00 Jim Lemon <drjimlemon at gmail.com>: > Hi

## Question1: How to define IV with interaction alone, without main effects? ## Question2: Should Type III ANOVA in package car be independent of the factor level order? ## data from http://www.otago.ac.nz/sas/stat/chap30/sect52.htm drug <- c(t(t(rep(1,3)))%*%t(1:4)); disease <- c(t(t(1:3)) %*% t(rep(1,4))); y <- t(matrix(c( 42 ,44 ,36 ,13 ,19 ,22 ,33 ,NA ,26 ,NA ,33 ,21 ,31 ,-3 ,NA

The loop : AllMAFs <- list() for (i in length(SeparatedGroupsofmealsCombs) { AllMAFs[[i]] <- apply( SeparatedGroupsofmealsCombs[[i]], 2, function(x)maf( tabulate( x+1) )) } gives these errors (I tried this many times and I'm sure I copied it entirely) :- Error in apply(SeparatedGroupsofmealsCombs[[i]], 2, function(x) maf(tabulate(x + : object 'i' not found > }

R-help, I have a data frame: > mydata strata nh Nh Wh fh 1 I 10 26 0.048 0.385 2 II 32 84 0.154 0.381 3 III 16 42 0.077 0.381 4 IV 4 11 0.020 0.364 5 V 10 26 0.048 0.385 7 VII 64 168 0.309 0.381 8 VIII 49 129 0.237 0.380 9 IX 22 58 0.107 0.379 91 VI 0 0 0.000 0.000 and I wish to rearrange the data are sorted according to the roman

Below. -- Bert Bert Gunter On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: > I have two ideas about it. > > 1- > i) Entering variables in quadratic form is done with the command I > (variable ^ 2) - > plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = > "LOO" > You could also use a new variable

Hi all, I?m trying to plot this data N M W I 10 106 II 124 484 III 321 874 IV 777 1140 V 896 996 VI 1706 1250 VII 635 433 VIII 1437 654 IX 693 333 X 1343 624 XI 1221 611 XII 25 15 XIII 3 XIV 7 8 So that in de Y axis will be the level (qualitative data) and in the X axis will be M and W variables. So x axis will be wwith a lenght between 0 and 2000. I would like to plot a line with M and other

Dear all, I have a couple of questions regarding the survival:::cch function. 1) I notice that Prentice and Self-Prentice functions are giving identical standard errors (not by chance but by programming design) while their estimates are different. My guess is they are both using the standard error form from Self and Prentice (1986). I see that standard errors for both methods are