similar to: Hi, Coding problem

On 2020-04-27 18:45, Jeremy Allison via samba wrote: > On Mon, Apr 27, 2020 at 10:27:17AM +0200, A L via samba wrote: >> On 2020-04-26 19:46, Jeremy Allison via samba wrote: >>> On Sun, Apr 26, 2020 at 11:51:42AM +0200, A L via samba wrote: >>>> * Connected from a Windows 10 computer over 1G ethernet. * Copy >>>> data using Windows Explorer and

Hi, there could you help me coding this problme? I am just starting to leard the R. So I really need help Question is from Ross, Simulation, 4th Edition. ch3 14. with x1=23, x2=66 Xn=3*Xn-1+5*Xn-2 mod(100) n>=3 we will call the sequence Un=Xn/100 n>=1 find the first 14 values thank you sophia

On 2020-04-29 00:40, Jeremy Allison via samba wrote: > On Mon, Apr 27, 2020 at 11:21:35PM +0200, A L wrote: >> I set up the following test case: >> * Linux 5.7-rc3 (with the patch from previous mail) >> * samba-4.12.1 >> * gcc-9.3.0 >> * liburing-0.6 >> * glibc-2.30-r8 >> >> ================================= >> Test 1) >> Copy 10 10GB

Dear r-helpers, I can run the examples on the mcsamp help page. For example: **************************************** > M1 <- lmer (y1 ~ x + (1|group)) > (M1.sim <- mcsamp (M1)) fit using lmer, 3 chains, each with 1000 iterations (first 500 discarded) n.sims = 1500 iterations saved mean sd 2.5% 25% 50% 75% 97.5% Rhat n.eff beta.(Intercept)

On 2020-04-26 19:46, Jeremy Allison via samba wrote: > On Sun, Apr 26, 2020 at 11:51:42AM +0200, A L via samba wrote: >> * Connected from a Windows 10 computer over 1G ethernet. * Copy data >> using Windows Explorer and FastCopy(1) from the Samba share to a >> local disk. * Verify the sha-256 sum on the files. From what I can >> see there is data corruption on many of

Hi, I'm trying the brlr function in a penalized logistic regression function. However, I am not sure why I am encountering errors. I hope to seek your advice here. (output below) Thank you! Your help is truly appreciated. Min-Han #No error here, the glm seems to work fine >

Dear guRus, I am trying to replace "~" by "$\sim$" for TeX. However, I can't get the backslash to work. I would like to turn "DV~IV" into "DV$\sim$IV". sub("~","$\sim$","DV~IV") => "DV$sim$IV" sub("~","$\\sim$","DV~IV") => "DV$sim$IV"

Dear all, I have a matrix called combine86 which looks as follows: > combine86 Sim Mean Obs Mean Sim Sum Obs Sum AMAZON 1172.0424 1394.44604 553204 659573 NILE 262.4440 164.23921 67973 41881 CONGO 682.8007 722.63971 205523 214624 MISSISSIPPI 363.0758 142.59883 124535 49054 AMUR 143.5857 89.30434 36040 22594 PARANA

Hi, I have a large data frame and within this there is one column which contains individual codes (eg. 1.1234.2a.2). I am splitting these codes into their 4 components using strsplit (eg. "1", "1234", "2a", "2"). However there are some individual codes which do not have a last component (eg. 2.4356.3b. ), I want to give these codes a "1" as their

Dear List, I am relatively new to R and am trying to create more attractive plots than excel can manage! I have looked through the various programmes ggplot, lattice, hmisc etc but my case seems to be not metnioned, maybe it is but i have not noticed - if this is the case i apologise.

Hi, i have a strange situation: A domain is still running where domblklist points to a snapshot file and also dumpxml says the current drive is that snapshot file. But the file has been deleted hours ago. And the domain is still running. I can login via ssh, the database and the webserver are still running, domain is performant. How can that be ? Also lsof shows that the file is deleted:

Hi all Is there any reason why the parameter i in a "for" loop ignores a value of zero? For example sim=c() p=.2 for(i in 0:5) {sim[i]=dbinom(i,5,p) } sim [1] 0.40960 0.20480 0.05120 0.00640 0.00032 In this example the quantile i= 0 was ignored since dbinom(0,5,p) [1] 0.32768 The same behaviour occurs if I use a while loop to perform the same calculation: sim=c() p=.2 i=0

Dear all, I have a data frame with one factor and four numeric variables and wish to obtain the var-cor matrix separately by factor. I tried by() and sapply() but getting nowhere. I understand this can be done by subsetting the dataframe, but there should have some sleek ways of doing it. Here is a simulated dataframe; s <- rep(c("A","B","C"), c(25,22,18)) d

Dear r-helpers, Spencer Graves and Manual Morales proposed the following methods to simulate p-values in lme4: ************preliminary************ require(lme4) require(MASS) summary(glm(y ~ lbase*trt + lage + V4, family = poisson, data = epil), cor = FALSE) epil2 <- epil[epil$period == 1, ] epil2["period"] <- rep(0, 59); epil2["y"] <- epil2["base"]

Dear R-users, I would like to show you a simple example that gives an overview of one of my current issue. Although my working setting implies a different parametric model (which cannot be framed in the glm), I guess that what I'll get from the following example it would help for the next steps. Anyway here it is. Firstly I simulated from a series of exposures, a series of deaths (given a

Hi, Can anyone help sort out the problem with the following script - I am a R newbie and I am self taught. obs.all = c() for(i in 1:386){ if (n.sim[i]>0){ obs = (1:133429)[event.details[,2] == i] obs.all = c(obs.all, sample(obs[obs < n.sim[i]], size = n.sim[i], replace=T)) } Basically, in the sample bit, I only want to get obs.all if the value of

In some time series simulations I'm doing, I occasionally want the model to be ``white noise'', i.e. no model at all. I thought it would be nice if I could fit this into the arima.sim() context, without making an exceptional case. I.e. one ***could*** do something to the effect if(length(model)==0) x <- rnorm(n) else x <- arima.sim(model,n) but it would be more suave if one

i have combined all the variables in a matrix, and i wish to conduct a simulation row by row. But i found out the code only works for the every first row after a cycle of nine samples. But after check out the code, i don know where is my mistake... can anyone pls help .... #For gamma disribution with equal skewness 1.5 #to evaluate the same R function on many different sets of data

Hello all. I am trying to run PAN, multilevel multiple imputation program, in R to impute missing data in a longitudinal dataset. I could successfully run the multiple imputation when I only imputed one variable. However, when I tried to impute a time-varying covariate as well as a response variable, I received an error message, “Error: subscript out of bounds.” Can anyone tell if my commands

Dear all, I have been trying to investigate the behaviour of different weights in weighted regression for a dataset with lots of missing data. As a start I simulated some data using the following: library(MASS) N <- 200 sigma <- matrix(c(1, .5, .5, 1), nrow = 2) sim.set <- as.data.frame(mvrnorm(N, c(0, 0), sigma)) colnames(sim.set) <- c('x1', 'x2') # x1 & x2 are