similar to: How to use a function inside a regression formula

Dear All, probably a simple enough solution but don;t seem to be able to get my head around it...example based on a publicly available data set: mydata <- read.csv("https://stats.idre.ucla.edu/stat/data/binary.csv") mylogit <- glm(admit ~ gre + gpa + rank, data = mydata, family = "binomial") library(effects) plot(allEffects(mylogit) ? ?

Hello everyone! I'm trying to get tinc running, but couldn't make it until now... My current situation is: all tincs are connected, but there ist (almost) no traffic: Only two PCs are able to ping to another, but not to itself. Let me explain, what I'm planning to do: I've got four networks: PROM: 10.69.0.0/16 PAN: 192.168.30.0/24 (I'm afraid, I can't change PAN to

I am working on a reproducible computing platform for which I would like to be able to _exactly_ reproduce an R object. However, I am experiencing unexpected randomness in some calculations. I have a hard time finding out exactly how it occurs. The code below illustrates the issue. mylm1 <- lm(dist~speed, data=cars); mylm2 <- lm(dist~speed, data=cars); identical(mylm1, mylm2); #TRUE

I am trying to follow this example for multinomial logistic regression http://www.ats.ucla.edu/stat/r/dae/mlogit.htm However, I cannot get it to work properly. This is the output I get, and I get an error when I try to use the mlogit function. Any ideas as to why this happens? > mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/mlogit.csv")) > attach(mydata) >

Hi all - my first time here and am having an issue with the Predict function. I am using a tutorial as a guide, locate here: http://www.ats.ucla.edu/STAT/R/dae/mlogit.htm My code gives this error > newdata1$predicted <- predict(mlogit,newdata=newdata1,type="response") Error in `$<-.data.frame`(`*tmp*`, "predicted", value = c(0.332822934960197, : replacement has

Sorry bit of a Newbie question, and I promise I have searched the forum already, but I'm getting a bit desperate! I have over-dispersed, zero inflated data, with variance greater than the mean, suggesting Zero-Inflated Negative Binomial - which I attempted in R with the pscl package suggested on http://www.ats.ucla.edu/stat/R/dae/zinbreg.htm However my data is non-integer with some pesky

Dear All, I am recycling a previous email of mine where I asked some questions about clustering mixed numerical/categorical data. This time I am more into data mining. I am given a set of known statistical indexes {s_i}, i=1,2...N for a N countries. These indexes in general are a both numerical and categorical variables. For each country, I also have a property x_i whose value is known, but

Hi everyone, If I compute a "Ordered Logistic or Probit Regression" with the polr function from MASS package. the summary give me : coefficients, Standard error and Tvalue.. but not directly the p.value. I can compute "manualy" the Pvalue, but Is there a way to directly obtain the pa.value, and I wonder why the p.valeu is not directly calculated, is there a reason? exemple

Hi, I am new to R and has been depending mostly on the online tutotials to learn R. I have to deal with zero inflated negative binomial distribution. I am however unable to understand the following example from this link http://www.ats.ucla.edu/stat/r/dae/zinbreg.htm The result gives two blocks. *library(pscl) zinb<-zeroinfl(count ~ child + camper | persons, dist = "negbin", EM =

Hi, I have the following setup. Two linux systems with two [test] external interfaces encrypted with ipsec [transport]. Two gre tunnels that pass 10.200.0.0/24 and 10.200.1.0/24 network traffic. Testing the balanced tunnels I would setup iptraf on one and ping from the other. The results would be as expected; traffic would be split between the two interfaces. Testing with an ftp transfer of

Hi all ! I would like to simulate spatial lattice/areal data with a conditional autoregressive (CAR) structure, for a given neighbouring matrix and for a autocorrelation "rho". Is there any package or function in R to perform it ? I found the function "CARsimu" in the hdeco library, but this is not what I'm looking for Thanks in advance Dae-Jin --

Hi List, FYI. We have been using CentOS 6.4 and have 2 vpn/gre tunnels to separate cisco rtrs using ospf. with kernel 2.6.32-358.23.2 We have upgraded to 6.5 bit using kernel 2.6.32-431.5.1 and the exact same configuration scripts for our vpn/gre tunnels. What I see is the first gre tunnel works great and I get an ospf neighbor. The second tunnel comes up and I can ping across it and I see

Hello Lartc Mailing List: Been working on something the last week and a half and ALMOST have it working.., just need a few pointers from the wizards on this mailing list to nail it. Ok, my setup is a hub and spoke arrangement, hub is Cisco 2821 with IOS 12.4. Spokes are ruggencom RX1000 routers, Debian based with the following versions installed: rx1000test:~# uname -a Linux rx1000test

On Tue, Dec 25, 2018 at 05:43:25PM +0800, Jason Wang wrote: > > On 2018/12/25 ??1:41, Michael S. Tsirkin wrote: > > On Mon, Dec 24, 2018 at 11:43:31AM +0800, Jason Wang wrote: > > > On 2018/12/14 ??9:20, Michael S. Tsirkin wrote: > > > > On Fri, Dec 14, 2018 at 10:43:03AM +0800, Jason Wang wrote: > > > > > On 2018/12/13 ??10:31, Michael S. Tsirkin

On Tue, Dec 25, 2018 at 05:43:25PM +0800, Jason Wang wrote: > > On 2018/12/25 ??1:41, Michael S. Tsirkin wrote: > > On Mon, Dec 24, 2018 at 11:43:31AM +0800, Jason Wang wrote: > > > On 2018/12/14 ??9:20, Michael S. Tsirkin wrote: > > > > On Fri, Dec 14, 2018 at 10:43:03AM +0800, Jason Wang wrote: > > > > > On 2018/12/13 ??10:31, Michael S. Tsirkin

On Wed, Dec 26, 2018 at 01:43:26PM +0800, Jason Wang wrote: > > On 2018/12/26 ??12:25, Michael S. Tsirkin wrote: > > On Tue, Dec 25, 2018 at 05:43:25PM +0800, Jason Wang wrote: > > > On 2018/12/25 ??1:41, Michael S. Tsirkin wrote: > > > > On Mon, Dec 24, 2018 at 11:43:31AM +0800, Jason Wang wrote: > > > > > On 2018/12/14 ??9:20, Michael S. Tsirkin

I want to test whether the proportional odds assumption for an ordered regression is met. The UCLA website points out that there is no mathematical way to test the proportional odds assumption (http://www.ats.ucla.edu/stat//R/dae/ologit.htm), and use graphical inspection ("We were unable to locate a facility in R to perform any of the tests commonly used to test the parallel slopes

Dear All, I have some questions about probit regressions. I saw a nice introduction at http://bit.ly/bU9xL5 and I mainly have two questions. (1) The first is almost about data manipulation. Consider the following snippet ################################################## mydata <- read.csv(url("http://www.ats.ucla.edu/stat/r/dae/binary.csv")) names(mydata) <-

Hi, Does anyone tried to get ipip or gre tunnel behind NAT environments. ? i''m trying to make both side tunneling with ipip or gre with private address just like belows.. A -------------------FIRWWAL -------------------INET ------------------- B PRIVATE PUBLIC PUBLIC (10.100.0.1) (211.xxx.xxx.xxx) (

Hello, Here is my network: ------------------ ------------- ----------- Linux box ----------- GRE --------- Cisco ---------- ------------------ ------------- What I wan to accomplish. I want ripv2 to go across (both ways) through the GRE tunnel. No packets are being passed thought the GRE