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...t of my office right now but I'll back to work next week and I will be able to explain in more detail how the applications I tied together work with RExcel and R. You can download the latest staconnDCOM.latest.exe from this site: http://rcom.univie.ac.at/ --- On Sun, 10/4/09, Ryusuke Kenji <ryusukekenji at hotmail.com> wrote: > From: Ryusuke Kenji <ryusukekenji at hotmail.com> > Subject: Apply R in Excel through RExcel > To: elaine.mcvey at gmail.com, mazatlanmexico at yahoo.com > Date: Sunday, October 4, 2009, 9:55 AM > > > > > > Hi Elaine and Felipe,...

I am facing the same problem as well, I would like to code with following concept but wondering how to cope it. if (*mdb file exist) { add new row/col } else { add new *mdb file } ---------------------------------------------------------------------------------------------- From: Uri Shimron <UriShimron_at_optiver.com> Date: Thu 21 Sep 2006 - 13:27:35 GMT First of all,

[code]>require("survival") > coxph(Surv(futime,fustat)~age + strata(rx),ovarian) Call: coxph(formula = Surv(futime, fustat) ~ age + strata(rx), data = ovarian) coef exp(coef) se(coef) z p age 0.137 1.15 0.0474 2.9 0.0038 Likelihood ratio test=12.7 on 1 df, p=0.000368 n= 26, number of events= 12 > coxph(Surv(futime,fustat)~age, ovarian, subset=rx==1)

6.4.1 Estimation of fixed effects Heterogeneous team ability is a possible explanation for the result in Section 6.3. That result simply indicates that the more goals a team scores, the higher the probability that it will score more. However, teams that can score more goals also indicate teams with greater ability, or just greater scoring ability, than their opponents. As mentioned in Section

Hi All, con <- member <- class <- list() for(i in 1:5) { con[[i]] <- odbcConnectAccess(paste("C:/Desktop/Data/source",i,".mdb",sep = '')) #read data from Access files member[[i]] <- sqlFetch(con[[i]],'member') #get table data from *.mdb files observe[[i]] <- sqlFetch(con[[i]],'observe') #get table data from *.mdb

Hi All, First method:- >library(XML) >theurl <- "http://home.sina.com" >download.file(theurl, "tmp.html") >txt <- readLines("tmp.html") >txt <- htmlTreeParse(txt, error=function(...){}, useInternalNodes = TRUE) >g <- xpathSApply(txt, "//p", function(x) xmlValue(x)) >head(grep(" ", g, value=T)) [1] " |

Hi experts, http://r.789695.n4.nabble.com/file/n4034318/Parametric_survival_analysis_2nd-order_efffect.JPG Parametric_survival_analysis_2nd-order_efffect.JPG As we know a normal survival regression is the equation (1) Well, I'ld like to modify it to be 2nd-order interaction model as shown in equation(2) Question: Assume a and z is two covariates. x = dummy variable (1 or 0) z = factors

To R programming experts, I am a undergraduate student, and now doing research personally. I apply diagonal bivariate poisson (R package "bivpois") with stochatics weighted function (refer to dixoncoles97 section 4.5 to 4.7). However I dont know how to fit this stochatical weighted function to the completed bivariate poisson model. I know that some other references for dynamic soccer

Assume that we collect below data : - subjects = 20 males + 20 females, every single individual is independence, and difference events = 1, 2, 3... n covariates = 4 blood types A, B, AB, O http://r.789695.n4.nabble.com/file/n4245397/CodeCogsEqn.jpeg ?m = hazards rates for male ?n = hazards rates for female Wm = Wn x ?, frailty for males, where ? is the edge ratio of male compare to female Wn =