similar to: References about dot a files

Hello Dear, I am trying to generate samples by using Monte Carlo simulation. For example, 1000 samples, Exponential distribution (f(x), lambda=0.0005, 0<=x<=360) Is there any package for Monte Carlo or just use random sample generation function? Many thank you for your help in advance, Jin -- View this message in context:

Hello, I am a new user of R and found the function dtnorm() in the package msm. My problem now is, that it is not possible for me to get the mean and sd out of a sample when I want a left-truncated normal distribution starting at "0". fitdistr(x,dtnorm, start=list(mean=0, sd=1)) returns the error message "Fehler in "[<-"(`*tmp*`, x >= lower & x <= upper,

Dear All, I have two questions regarding distribution fitting. I have several datasets, all left-truncated at x=1, that I am attempting to fit distributions to (lognormal, weibull and exponential). I had been using fitdistr in the MASS package as follows: fitdistr<-(x,"weibull") However, this does not take into consideration the truncation at x=1. I read another posting in this

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Hi Rs, I am analyzing a time to event dataset with several competing risks. 0 = Active by end of study 1 = Stopped treatment to start another treatment 2 = Lost 3 = Dead My event of interest in Lost to Followup but starting a different treatment and dying are competing risks. All 1,2,3 events are events of exiting the study, but it's only 2-LTFU that we are concerned with (I know I am

Hi, all How can generate a sample from truncated inverse gamma distribution in R? thanks

Hello, I want to fit a distribution to a dataset. Important is not the "overall" fitting but the fitting in the tail (e.g. all observations > x or the n highest values). Standard ML-estimation sometimes doesn't work here very well. We see that especially when we have truncated datasets the algorithms won't converge. In the case of lognormal distribution: It seems that the

Hi. I am looking for a function for left-truncated data. I have one data set with 2 variables (Hours~Yrs_Ed). I already left-censored the data at 200 and left-truncated it at the same spot, so that I am able to make 2 estimations (one for censoring and one for truncation). I know how to make the linear regression for the left-censored variable (hours) and how to plot the regression line into the

Hi, How can I access the Values stored in kpssstat-class given by KPSS.test function and store it in a variable. For example: >x <- rnorm(1000) >test <- KPSS.test(ts(x)) >test ---- ---- KPSS test ---- ---- Null hypotheses: Level stationarity and stationarity around a linear trend. Alternative hypothesis: Unit root. ---- Statistic for the null

Jani Nikula (4): drm/amdgpu: fix -Wformat-truncation warning in amdgpu_gfx_kiq_init_ring() drm/nouveau: fix -Wformat-truncation warning in nouveau_backlight_init() drm/imx: fix -Wformat-truncation warning in imx_ldb_probe() drm: enable -Wformat-truncation across the subsystem drivers/gpu/drm/Makefile | 3 +-- drivers/gpu/drm/amd/amdgpu/amdgpu_gfx.c | 6

Do you know of any references that verify the accuracy of R for basic statistical calculations and tests. The results of these studies should indicate that R results are the same as the results of other statistical packages to a certain number of decimal places on some benchmark calculations. Thanks, Corey Powell Clinical Data Analyst Broncus Technologies cpowell@broncus.com [[alternative

Hello, For the very first time, I tried the command bellow on a newly build Debian Buster box on which I successfully built Asterisk 17.2.0 before. I got : # contrib/scripts/install_prereq install-unpackaged *** Installing NBS (Network Broadcast Sound) *** A nbs-trunk/LICENSE A nbs-trunk/nbsclient.c A nbs-trunk/nbsd.c A nbs-trunk/nbs.h A nbs-trunk/nbscat.c A nbs-trunk/Makefile

On 28.05.2018 11:07, G?bor Cs?rdi wrote: > stdin() is not the same as file("stdin"), see the note in ?stdin. In particular stdin() works in an interactive session but not when R -f / Rscript is used, since it does not wait for the user to input anything: $ R -f readLines.R R version 3.5.0 (2018-04-23) -- "Joy in Playing" Copyright (C) 2018 The R Foundation for Statistical

I am creating a package, and a rather long usage line for one function becomes truncated in the generated .pdf manual. Is there a way that I can prevent that truncation?

No, that will make it even worse since you'll be declaring a lot more memory that you actually have. The real problem is that you're ignoring the truncation, so you probably want to use something like if (snprintf(tempname, sizeof(tempname), "%s.%d", of1name, j) >= sizeof(tempname)) Rf_error("file name is too long"); BTW: most OSes systems have a path limits that

Hi Guys, Thanks for the interest in the xen hypervisor debugger, prev known as kdb. Btw. I''m gonna rename it to xdb for xen-debugger or hdb for hypervisor debugger. KDB is confusing people with linux kdb debugger and I often get emails where people think they need to apply linux kdb patch also... Anyways, attaching patch that is cleaned up of my debug code that I accidentally left in

I have Gentoo host where `ifconfig -a` prints long interface names truncated to 9 chars (there is closed bug report [1]). Unfortunately, `facter` uses `ifconfig -a` output to get list of interface names and because of truncation it generates `interfaces` fact with incorrect interface names. Also it fails to retrieve individual interface information with following message for each interface with

Hello, maybe that my Question is a "beginner"-Question, but up to now, my research didn't bring any useful result. I'm trying to fit a distribution (e.g. lognormal) to a given set of data (ML-Estimation). I KNOW about my data that there is a truncation for all data below a well known threshold. Is there an R-solution for an ML-estimation for this kind of data-problem? As

Hi, is there any package (or source code snippet) that will evaluate the Frechet distance for curves represented as sets of points? Searching around only threw up references to a Frechet distribution. Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at psu.edu> <http://jijo.cjb.net> GPG Fingerprint: 0CCA 8EE2 2EEB 25E2 AB04 06F7 1BB9