similar to: How to display full name for the coefficients/factors in summary()?

Hi all: Here's a question about result of loglinear analysis. There're 2 factors:area and nation.The raw data is in the attachment. I fit the saturated model of loglinear with the command: glm_sat<-glm(fre~area*nation, family=poisson, data=data_Analysis) After that,I extract the coefficients: result_sat<-summary(glm_sat) result_coe<-result_sat$coefficients I find that all the

I am trying to store regression objects in a data.table df <- data.frame(x = rnorm(20)) df[, "y"] <- with(df, x + 0.1 * x^2 + 0.2 * rnorm(20)) mydt <- data.table(mypower = c(1, 2), myreg = list(lm(y ~ x, data = df), lm(y ~ x + I(x^2), data = df))) mydt #?? mypower??? myreg #???? <num>?? <list> #1:?????? 1 <lm[12]> #2:?????? 2 <lm[12]> But mydt[1, 2]

Dear R-users, I'm finding for a R-package concerning graphs. Is there some kind of that package? I've a set of correlation coeffients between several variable and I wish to built a graph to link variables correlated. Many thanks. Best, Vito ===== Diventare costruttori di soluzioni "The business of the statistician is to catalyze the scientific learning process." George

Hello , I want to compare two quadratic regression models with non-parametric bootstrap. However, I do not know which R package can serve the purpose, such as boot, rms, or bootstrap, DeltaR. Please kindly advise and thank you. Elaine The two quadratic regression models are y1=a1x^2+b1x+c1 y1= observed migration distance of butterflies() y2=a2x^2+b2x+c2 y2= predicted migration distance of

Well, you may have good reasons to do things this way -- and you certainly do not have to explain them here. But you might wish to consider using R's poly() function and a basic nested list structure to do something quite similar that seems much simpler to me, anyway: x <- rnorm(20) df <- data.frame(x = x, y = x + .1*x^2 + rnorm(20, sd = .2)) result <- with(df,

I've been writing a bunch of simulation experiments to test models in MASS (glm.nb) and JK Lindsey's repeated library (gar and kalcount). If I generate data over and over, and estimate a model for each, I end have syntax like this: x <- rnorm(1000) for (i in 1: nOfRuns){ y <- getPhonyData(x) estim <- glm.nb(y~x,link="log") } Except for problems of nonconvergence

Hi, I conduct a univariate regression with lm function. I would like to get the p value for the regression. Is there a method that would enable me to extract the p value into a variable. Thanks. Arjun Bhandari ************************************************************************************************************** This email and any files transmitted with it are confidentia...{{dropped}}

Thanks everyone for their responses. My data is organized in a data.table.? My goal is to perform analyses according to some groups.? The results of analysis are objects.? If these objects could be stored as elements of a data.table, this would help downstream summarizing of results. Let me try another example. carsdt <- setDT(copy(mtcars)) carsdt[, unique(cyl) |> length()] #[1] 3

Dear ALL, I use BEKK package to estimate Bivariate GARCH model. But when the results come out, there's no t-stat or p-value of the estimated coeffients. Does anyone know how to get the significance? Followings are the codes I input, >P1=data.frame(x,y) >y1=mvBEKK.est(P1) >mvBEKK.diag(y1) Anyhelp would be appreciated! Sincere, Zoe -- View this message in context:

Hello, I am work with two quadratic regression models y=ax^2+bx+c with the function of lm. y1= observed migration distance of butterflies(y1=a1x^2+b1x+c1) y2= predicted migration distance of butterflies (based on body mass) (y2=a2x^2+b2x+c2) x= body mass of butterflies Now I would like to check the two regression model differ by testing if the coeffients (a, b, c) of the y1 and the y2

Hi there, I have a predictor varible "class" which is a categorical variable and a ' coxph' is used to find the coeffients. How can I plot the predicted survival proportion based on this model? Thanks Lisa Wang Princess Margaret Hospital Toronto tel 416 946 4501

Hello, I have the following Xen 3.0.2-2 related problem: A host system with Centos 4.4 in the dom0, guest systems are Fedora Core 5 (images from jailtime.org) mounted on LVM. Networking on the domUs is not working, Iptables in the guests are not working either. Each Guest system should have at least 1 dedicated public IP assigned to it, but should have the capability to have more than 1

Currently doing some work on local maxima on a random field and have encountered an issue with the Miwa algorithm used with the pmvnorm function in the mvtnorm R package. Based on recommendations by Mi et al., we ran the mvtnorm package using the Miwa algorithm, since we have a maximum of 4 dimensions with non-singular matrices. However, running the estimation procedure in this way, we obtained

Rather specialized. As this appears to be primarily a statistical, not an R programming question, you may do better posting on a statistical site like http://stats.stackexchange.com/ if you don't get a satisfactory reply here . Alternativey, if you think this is a package bug, perhaps contact the package maintainer directly, as (s)he may not monitor this list. -- Bert Bert Gunter

Good point. Now this returns 0.04062184. Hmmm..... On Mon, Oct 2, 2017 at 6:30 PM, Hollie Johnson (PGR) < h.a.johnson at newcastle.ac.uk> wrote: > Hi Eric, > > > Thanks for having a look into this. I think you have a small typo... > > B <- matrix(x, nrow=3, byrow = TRUE) should read B <- matrix(y, nrow=3, > byrow = TRUE) > > > Regards, Hollie >

Hi Eric, Thanks for having a look into this. I think you have a small typo... B <- matrix(x, nrow=3, byrow = TRUE) should read B <- matrix(y, nrow=3, byrow = TRUE) Regards, Hollie ________________________________ From: R-help <r-help-bounces at r-project.org> on behalf of Eric Berger <ericjberger at gmail.com> Sent: 02 October 2017 16:16:13 To: Bert Gunter Cc: r-help at

I apologize that I've asked a similar question before, but being new to R I don't think I did a very good job of formating the question. I've included a text file since the date set is somewhat large. What I have is a huge string of numbers in a text file. The numbers are all separated by comma's and the groups are separated by a semicolon. What I would like to do is read each

Hello , I have estimated the following model, a sarima: p=9 d=1 q=2 P=0 D=1 Q=1 S=12 In R 2.12.2 Call: arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), optim.control = list(reltol = tol)) Coefficients: ar1 ar2 ar3 ar4 ar5 ar6 ar7 ar8 ar9 0.3152 0.8762 -0.4413 0.0152 0.1500 0.0001 -0.0413 -0.1811

Hi, Am I hitting some limit in match? Consider the following example: > tst<-seq(100,125,by=.2)%in%seq(0,800,by=.1) > sum(tst) [1] 76 > seq(100,125,by=.2) [1] 100.0 100.2 100.4 100.6 100.8 101.0 101.2 101.4 101.6 101.8 102.0 102.2 [13] 102.4 102.6 102.8 103.0 103.2 103.4 103.6 103.8 104.0 104.2 104.4 104.6 [25] 104.8 105.0 105.2 105.4 105.6 105.8 106.0 106.2 106.4 106.6 106.8

Hi, Am I hitting some limit in match? Consider the following example: > tst<-seq(100,125,by=.2)%in%seq(0,800,by=.1) > sum(tst) [1] 76 > seq(100,125,by=.2) [1] 100.0 100.2 100.4 100.6 100.8 101.0 101.2 101.4 101.6 101.8 102.0 102.2 [13] 102.4 102.6 102.8 103.0 103.2 103.4 103.6 103.8 104.0 104.2 104.4 104.6 [25] 104.8 105.0 105.2 105.4 105.6 105.8 106.0 106.2 106.4 106.6 106.8