search for: 0.623

I wonder if the 'sep' argument in reshape() is being ignored unintentionally: ## From example(reshape) df <- data.frame(id=rep(1:4,rep(2,4)), visit=I(rep(c("Before","After"),4)), x=rnorm(4), y=runif(4)) reshape(df, timevar="visit", idvar="id", direction="wide", sep = "_") id x.Before

I submit the following matrix to both MATLAB and R x= 0.133 0.254 -0.214 0.116 0.254 0.623 -0.674 0.139 -0.214 -0.674 0.910 0.011 0.116 0.139 0.011 0.180 MATLAB's inv(x) provides the following 137.21 -50.68 -4.70 -46.42 -120.71 27.28 -8.94 62.19 -58.15 6.93 -7.89 36.94 8.35 11.17 10.42 -14.82 R's solve(x) provides: 261.94 116.22 150.92 -267.78 116.22 344.30 286.68

Hi all, Using: R version 2.8.1 Patched (2009-03-07 r48068) on OSX (10.5.6) with survival version: Version: 2.35-3 Date: 2009-02-10 I get the following using the first example in ?summary.survfit: > summary( survfit( Surv(futime, fustat)~1, data=ovarian)) Call: survfit(formula = Surv(futime, fustat) ~ 1, data = ovarian) time n.risk n.event survival

Hello: In the example below (or for a censored data) using survfit.coxph, can anyone point me to a link or a pdf as to how the probabilities appearing in bold under "summary(pred$surv)" are calculated? Do these represent acumulative probability distribution in time (not including censored time)? Thanks very much, parmee *fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)*

Can anyone help explain to me why the two codes below have different result? I thought I can use log(time)~. to replace log(time)~dist+climb+timef.I am using CVlm from DAAG package. I think nihills is preloaded with the package. Thanks in advance. > CVlm(df=nihills, form.lm=formula(log(time)~.),plotit="Observed",m=2)Analysis of Variance Table Response: log(time) Df Sum Sq

Hola amigos, esta es mi primera duda, espero que no sea demasiado fácil. Tengo unos datos de dos variables y quiero mostrar recta de regresión y valor de correlación serie0 <- c(0.651, 0.712, 0.614, 0.645, 0.559, 0.647, 0.642, 0.534, 0.616, 0.621, 0.623) serie1 <- c(0.572, 0.641, 0.565, 0.596, 0.518, 0.604, 0.602, 0.501, 0.58, 0.589, 0.596) data <- cbind(serie0, serie1) colnames(data)

Dear R community members, I think I am asking a very simple question, but I really looked up in the faqs and manuals and found nothing helpful. I am trying to plot a data frame with the following structure (this is just a small extract): glo conc odor line series X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 1 0 AIR LN1 UP -0.488

Hi, In my analysis of impacts of insecticide-treated bednets on malaria, I look at the relationship between malaria incidence and mosquito behaviors. The condensed data set is copied here. Ordinary regression (lm) shows that Incidence was negatively related to Mortality. This makes sense because the latter reflected the strength of killing mosquitoes by insecticide-treated nets. Since the

Bueno, ya lo he solucionado gracias a Carlos me ha enviado un correo en privado (supongo que se ha despistado, si no lo querías hacer público ya es tarde) con esta info: -- Creo que lo tienes (en formato básico) aquí: https://stat.ethz.ch/pipermail/r-help/2007-November/146285.html Aunque pensaba que si tu objetivo último es el de que usuarios "potencialmente tontos" sean capaces de

Dear R-helpers, In my dataset I have two continuous variable (A and B) and one factor. I'm investigating the regression between the two variables usign the command lm(A ~ B, ...) but now I want to know the regression coefficient (r2) of A vs. B for every factors. I know that I can obtain this information with excel, but the factor have 68 levels...maybe [r] have a useful command. Thanks,

suppose I have two sets of vectors: x1,x2,...,xN and y1,y2,...,yN. I want N correlations: cor(x1,y1), cor(x2,y2), ..., cor(xN,yN). my sets of vectors are arranged as data frames x & y (vector=column): x <- data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10)) y <- data.frame(d=rnorm(10),e=rnorm(10),f=rnorm(10)) cor(x,y) returns a _matrix_ of all pairwise correlations: cor(x,y)

Hello, I’m trying to follow the syntax of a script from a journal website. In order to create a regression formula used later in the script, the regression matrix must have column names “X1”, “X2”, etc. I have tried to assign these column names to my matrix ScoutRSM.mat using a for loop, but I don’t know how to interpret the error message. Suggestions? Thanks, Paul

Hi all, Two questions: 1. Is there a way to evaluate models from lmer() with a poisson distribution? I get the following error message: library(lme4) lmer(tot.fruit~infl.treat+def.treat+(1|initial.size),family=poisson)->model plot(fitted(model),resid(model)) Error: 'resid' is not implemented yet Are there any other options? 2. Why doesn't the function estimable() in gmodels

I am using the coxph, survfit and summary.survfit functions to calculate an estimate of predicted survival with confidence interval for future patients based on the survival distribution of an existing cohort of subjects. I am trying to understand the calculation and interpretation of the std.err and confidence intervals printed by the summary.survfit function. Using the default confidence

Dear all I need to compute percentage changes of my data, but unfortunately they contain both negative and zero values, and I am quite confused on how to proceed. Searching the internet I found that many people ran into similar issues, with no obvious solution available. The last couple of weeks I've been playing with all the data transformations that I could think of. Below I will expose on

Below is a revised version of my kernel of functions for isolating R/S and operating system differences. The main change is "date" which I've renamed "date.parsed" to avoid conflicts with the R and S date functions. The R call now uses system() rather than unix() to avoid warning messages in R 0.62.3. Paul Gilbert

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

R gurus: I'm trying to get another round of rconifers out and I need some advice/help crushing differences in the examples test. I'm trying to make sure the max sdi values are being respected. I've added a tests/rconifers-Ex.Rout.save (from windows i386-pc-mingw32) and when I ran R CMD check (both R-2.13.0), I got the following results: * using log directory

Hello all, I would like to connect two IPv4-only networks through global IPv6-only network with tinc. Could anyone tell me how to configure tinc.conf and the other config files? Thanks in advance, Ichiro Tinc: Discussion list about the tinc VPN daemon Archive: http://mail.nl.linux.org/lists/ Tinc site: http://tinc.nl.linux.org/

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter