search for: cumulate

Hi, I am wondering if anyone can explain to me if cumulative incidence (CI) is just "1 minus kaplan-Meier survival"? Under what circumstance, you should use cumulative incidence vs KM survival? If the relationship is just CI = 1-survival, then what difference it makes to use one vs. the other? And in R how I can draw a cumulative incidence plot. I know I can make a Kaplan-Meier

hi y'all, I am wondering if there is any special command, function, package, etc to help me doing a cumulative distribution function, with y-scale - probability scale. I tried the help in R and i got the following answers: cumsum(base) Cumulative Sums, Products, and Extremes ecdf(stepfun) Empirical Cumulative Distribution Function cpgram(ts) Plot

Hi @all, I am biting my nails with the following problem: I have a data set of daily rainfall measurements for the last 20 years. What I want to do is calculate the daily cumulative sum of rainfall but only for every year which means that the cumulative sum has to be reset each year. After the calculations I want to plot each year of cumulative rainfall as a separate line in one graph preferably

...Benchmark\n") cat(" =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D\n") cat(c("Number of times each test is run__________________________: ", = runs)) cat("\n\n") cat(" I. Matrix calculation\n") cat(" ---------------------\n") flush.console() # (1) cumulate <- 0; a <- 0; b <- 0 for (i in 1:runs) { timing <- system.time({ a <- abs(matrix(rnorm(1200*1200, sd=3D0.1), ncol=3D1200, = nrow=3D1200)); b <- t(a); dim(b) <- c(600, 2400); a <- t(b) })[3] cumulate <- cumulate + timing } timing <- cumulate/runs t...

def webs @webs ||= Web.find(:all).inject({}) { |webs, web| webs.merge(web.address => web) } end -- Posted via http://www.ruby-forum.com/.

This one should be easy but it's giving me a hard time mostly because tapply puts the results in a list. I want to calculate the cumulative sum of a variable in a dataframe, but with the accumulation only within each level of a factor. For a very simple example, take: > df <- data.frame(x=c(rep(1,5),rep(2,5),rep(3,5)),fac=gl(3,5,labels=letters[1:3])) > df x fac 1 1 a 2 1 a

Dear List, ? I want to fit a CPH survival model with a time-dependent cumulative exposure variable. More specifically, I have exposure measurements for all cohort members at discrete times (yearly measurements) during follow-up. ? I suppose that when estimating the model parameters the most correct would be to have the cumulative exposure for everybody at risk at each death time, as I cannot

Dear R experts, beginners and everyone else, I'm calculating "cumulative periodogram" using the command "cpgram" [1] from the MASS library. Here is a short example with the "lh" (hormone level) dataset: library(MASS) plot(lh,type="l",ylab="value",xlab="time", main="Hormone Levels (lh)") spectrum(lh,

Hello there, I am using R to plot some cumulative histogram for my data. Please help in this case. Thank you Lisa Wang Princess Margaret Hospital Toronto phone 416 946 4501 ext.4883

Dear all, Is there a way to calculate the non-cumulative hazard (instantaneous hazard), which is the product of baseline hazard and exp{beta*covariate} ? I knew in survfit, we can get the estimator of cumulative baseline hazard, but how can we get the non-cumulative one? Thank you very much! Koshihaku -- View this message in context:

Hi, I have two variables ranging both from 0 to 1 (n=500 each). Now I am interested in plotting them both in one plot (using ggplot2). So far I used ecdf() (from an example I found with google) to get values for the cumulatice distribution function which gives a relative curve. I also want to do the same plot but using absolute cumulative values instead of relative. Can that be done with ecdf or

Hi, I am trying to create a Cumulative Frequency graph and I am using the following example: http://www.r-tutor.com/elementary-statistics/quantitative-data/cumulative-frequency-graph When I plot this data, how do I put in "real values" on the x-axis, rather than the values that are used for the breaks Thanks -- Shane [[alternative HTML version deleted]]

Hi list, this is my second try for first post on this list (I tried to post via email and nothing appeared in my email-inbox, so now I try to use the nabble-web-interface) - I hope that you will only have to read one post in your inbox! Okay, my question ... I was able to plot a histogram and add the density()-line to this plot. I was able to plot a cumulative form of this histogram. Yet, I was

Dear R-users, I am checking the proportional hazard assumption of a cox model for a given covariate, let say Z1, after adjusting for other relavent covariates in the model. To this end, I fitted cox model stratified on the discrete values of Z1 and try to get beslow estimator for the baseline cumulative hazard function (H(t)) in each stratum. As far as i know, if the proportionality assumption

I am trying to fit a nonlinear regression to infiltration data in order to determine saturated hydraulic conductivity and matric pressure. The original equation can be found in Bagarello et al. 2004 SSSAJ (green-ampt equation for falling head including gravity). I am also VERY new to R and to nonlinear regressions. I have searched the posts, but am still unable to determine why my data come up

Hello My dataset is as follows: jobno recruits 1100 18 1200 1 1850 5 2100 190 2789 25 3000 1 . . . . the dataset has 130 rows I want to plot barplot from left side and cumulative curve from right side in one graph itself using layers in ggplot2. I sorted the recruits 1st in decreasing order

Hello, not understanding the output of prcomp, I reduce the number of components and the output continues to show cumulative 100% of the variance explained, which can't be the case dropping from 8 components to 3. How do i get the output in terms of the cumulative % of the total variance, so when i go from total solution of 8 (8 variables in the data set), to a reduced number of

What is the R way of computing cumulative growth rates given a series of discrete values indexed . For instance, given a matrix of 20 observations for each of 5 series (zz), what is the most straight forward technique in R for computing cumulative growth (zzcum) ? It seems for the solution I'm after might be imbedding the following cum growth rate calc as a function into a function call

tl;dr in low data situations we don’t look at past information, and that increases the false positive regression rate. We should look at the possibly incorrect recent past runs to fix that. Motivation: LNT’s current regression detection system has false positive rate that is too high to make it useful. With test suites as large as the llvm “test-suite” a single report will show hundreds of

Dear R-Users, Did anyone follow more closely the SARS Cov-2 lineages? I have done a quick check of Cov-2 mutations on the list downloaded from NCBI (see GitHub page below); but it seems that the list contains the cumulative mutations only for B.1 => B.1.1, but not after the B.1.1 branch: # B.1 => B.1.1 seems cumulative diff.lineage("B.1.1", "B.1", data=z) # but B.1.1