similar to: selecting monotone pattern of missing data from a dataframe with mixed pattern of missingness

Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2

hie i'm tryimg to generate two survival data using the following code (I know its ugly ) but it seems to repeat two of the variables can any one tell me whats the porblem. n=20 n1=n/2 n2=n/4 a11=1 ;a12=1.4 ;a21=16 ;a22=a12 * a21 t1<-array(1,c(n1)) t2<-array(2,c(n1)) treatgrp=matrix(c(t1,t2))

hie when i use plot.survfit to plot more than one graph why I only see the last graph how do i see the other graphs.for example n=20 n1=n/2 n2=n/4 a11=4;a12=4 ;a21=4 ;a22=4 t1<-array(1,c(n1)) t2<-array(2,c(n1)) treatgrp=matrix(c(t1,t2))

hie Im trying to calculate the power of the logrank test for different values of rho .I was just wandering whether the following programme would do it. any suggestions are welcome s=50 number=1 count1=0;count2=0;count3=0;count4=0;count5=0;count6=0;count7=0;count7=0; count8=0;count9=0 while(s!=0){ n=20 n1=n/2

I'm working on getting the Darwin/Mac OS X port of Vorbis up and running again and have run into problems building libvorbisfile. I have installed the latest libtool (1.3.5) and modified it to handle Darwin/Mac OS X better (to create shared libraries, dylibs, that can be linked against other dylibs instead of creating bundles which cannot be used as input to the linker). But, when it tries

my program given below can some one make it presentable. I trying to simulate survival data and calculate the power. I think i could have done better. s=10 number=0 count1=0;count2=0;count3=0;count4=0;count5=0;count6=0;count7=0;count8=0; count9=0; count11=0;count22=0;count33=0;count44=0;count55=0;count66=0;count77=0; count88=0;count99=0; while(s!=0){ n=100 n1=n/2 n2=n/4

'time0.c' has been missing from the current CVS for the past few days, so the Vorbis Windows DLLs / Libs won't compile - here, anyway. <p><p>J. <p><p><p><p>--- >8 ---- List archives: http://www.xiph.org/archives/ Ogg project homepage: http://www.xiph.org/ogg/ To unsubscribe from this list, send a message to 'vorbis-dev-request@xiph.org'

I have 100+ .csv files which have the basic format: > test X Substance1 Substance2 Substance3 Substance4 Substance5 1 Time1 10 0 0 0 0 2 Time2 9 5 0 0 0 3 Time3 8 10 1 0 0 4 Time4 7 20 2 1 0 5 Time5

Here are some minor things I noticed when updating the vorbis module for GoldWave: Bitwise.c, line 175 and 207 Warning: Negative unsigned value ret=-1UL; Info.c, line 385 Warning: Unreachable code break; vorbisfile.c, line 1407 Warning: Call to function with no prototype int host_endian = host_is_big_endian(); fix: add 'void' to line 1339: static int host_is_big_endian( void )

I can successfully compile the libogg prebeta4 tarball, but when I try to compile libvorbis I get make[2]: Entering directory `/home/me/dl/libvorbis-1.0prebeta4/lib' /bin/sh ../libtool --mode=link gcc -O20 -ffast-math -mno-ieee-fp -D_REENTRANT -fsigned-char -DUSE_MEMORY_H -o libvorbis.la -rpath /usr/local/lib -version-info 0:1:1 mdct.lo smallft.lo block.lo envelope.lo window.lo lsp.lo

Le 30/09/2019 ? 16:17, Duncan Murdoch a ?crit?: > > There's a StackOverflow question > https://stackoverflow.com/q/22024082/2554330 that references this text > from ?missing: > > "Currently missing can only be used in the immediate body of the > function that defines the argument, not in the body of a nested > function or a local call. This may change in the

There is "missing with default" and "missing without default". If an argument x is missing without a default, then missing(x) is true, if you pass x to another function, it will pass the value of the "missing argument". (which is different than simply being missing!) If an argument x is missing _with_a default, then missing(x) is still true, but if you pass x to

Dear all, I generated a dataset with 500 unrelated individuals and 10 biallelic SNPs. From this dataset,I would like to create data with 5% missingness on genotype information at random and also data with 5% genotyping error. Can someone help me with how I can do it. [[alternative HTML version deleted]]

Hi all, I have a vector, most of which is missing. The data is always increasing, but may do so in jumps. I would like to interpolate the NAs with 'best guesses', using something like filter(), which doesn't work due to the NAs. Here is an example: > x <- c(2,3,NA,NA,NA,3.2,3.5,NA,NA,6,NA) > x [1] 2.0 3.0 NA NA NA 3.2 3.5 NA NA 6.0 NA I would like a function that

I have the R code at the end. The last command gives me "1 observation deleted due to missingness". I don't understand what this error message. Could somebody help me understand it and how to fix the problem? > summary(afit) Df Sum Sq Mean Sq F value Pr(>F) A 2 0.328 0.16382 0.1899 0.82727 B 3 2.882 0.96057 1.1136 0.34644 C

Dear R-List, My questions concerns missing values. Specifically, is is possible to use different "types" of missingness in a dataset and not a one-size-fits-all NA? For example, data may be missing because of an outright refusal by a respondent to answer a question, or because she didn't know an answer, or because the item simply did not apply. In later analysis it is sometimes

Dear R users,   I have the following problems. My dataset (dat) is as follows: a <- c(1,2,3) id <- rep(a, c(3,2,3)) stat <- c(1,1,0,1,0,1,1,1) g <- c(0,0,0,0,0,0,1,0) stop <- c(1,2,4,2,4,1,1.5,3) dat <- data.frame(id,stat,g,stop)   I want to creat a new dataset (dat2) with missing values such that when either g = =1 or stat = =0, the remaining rows for an individual subject

Hi I've simulated multivariate longitudinal. The data is a mixture of conitnous and categorical data. I've stored it in matrix form with the time dependent variables as colons. Now I want to create a monote missing data pattern starting of with MCAR-missingnes and different proportions of missingdata and then refine the function to handle MAR and NMAR. Is there anybody that could help or

Hello, i have a little problem with R and i hope you can help me. I want to use splines to estimate a function but i want to force the interpolation to be monotone. Is this possible with R ? Thank you, Rémi. --------------------------------- [[alternative HTML version deleted]]

Hello I am looking for a function to create an Integrated (I) spline basis, somehting similar to the likes of 'bs' and 'ns'. I have come across the funcitons, fda::eval.monfd Values of a Monotone Functional Data Object fda::/.fd FDA internal functions fda::monfn Evaluates a monotone function fda::smooth.monotone Monotone