search for: multistation

Hi, I've seen in the NestCohort package that one can do a hazard model with a binary outcome using covariates. I am interested in multistate hazard models with time-varying covariates, but can't seem to find this already implemented in an R package. Is this included somewhere but called something else? I feel like I've looked all over. Thanks! Michaela Gulemetova-Swan

Hi everyone, I am trying to run the example of multistate occupancy model from the book Bayesian Population Analysis using WinBUGS (Marc Kéry and Michael Schaub): This example is available on http://www.vogelwarte.ch/code-for-running-bpa-using-jags.html When I try to run the first line of this section of the model : # Initial values zst

Hello! I'm hoping that Gmail won't HTML format this mail so that I'll get flamed :) Anyway, my question relates to ssh_config. The problem I find is that the Host pattern is only applied to the argument given on the command line, as outlined in the man page: "The host is the hostname argument given on the command line (i.e. the name is not converted to a canonicalized host name

From: Sebastian Andrzej Siewior <sebastian at breakpoint.cc> The "zstd at breakpoint.cc" compression algorithm enables ZSTD based compression as defined in RFC8478. The compression is delayed until the server sends the SSH_MSG_USERAUTH_SUCCESS which is the same time as with the "zlib at openssh.com" method. Signed-off-by: Sebastian Andrzej Siewior <sebastian at

hello,everyone: I am now confused in multistate survival , when I want to poccess a multistate survival analysis, I turn to R and the package 'mstate' and packege 'cmprsk'. When I come to publishing the article. Follow requirement of the magzine, the statistic is carry out in LTA package (which was said to be a authority in intauterine from WHO) . There we found difference

I am getting a repeated error when I try to run a logistic regression in R 2.8.1 >(glm(prop1~x1,data=glm1,family=binomial("logit"),weights=nt1)) Error in model.frame.default(formula = prop1 ~ x1, data = glm1, weights = nt1, : invalid type (list) for variable 'x1' x1 is multistate categorical (3 categories). 2 of the categories have 12 observation, one has 9. Is this what

I tried to use ctree but am not sure about the meaning of the plot. My.data.ct<-ctree(Resp~., data=My.data) plot(My.data.ct) My data.frame contains 88 explanatory variables (continous,ordered/unordered multistate,count data) and one response with two groups. In the plot are only two variables shown (2 internal nodes) and 3 final nodes. Does it mean that only these two variables show a

I have a data frame that is 122 columns and 70000ish rows it is a zoo object, but could be easily converted or read in as something else. It is multiparameter multistation water quality data - there are a lot of NA s. I would like to find "chuncks" of data that are free of NA s to do some analysis. All of the data is numeric. Is there a way besides graphing to find these NA less "chuncks". I did not include data because of the size of the data...

Dear List, I am looking to perform exploratory analyses of two (relatively) large datasets of categorical data. The first one is a binary 80x100 matrix, in the form: matrix(sample(c(0,1),25,replace=TRUE), nrow = 5, ncol=5, dimnames = list(c( "group1", "group2","group3", "group4","group5"), c("V.1", "V.2", "V.3",

I added ZSTD support to OpenSSH roughly three years ago and I've been playing with it ever since. The nice part is that ZSTD achieves reasonable compression (like zlib) but consumes little CPU so it is unlikely that compression becomes the bottle neck of a transfer. The compression overhead (CPU) is negligible even when uncompressed data is tunneled over the SSH connection (SOCKS proxy, port

Hi R experts, I have a data recoding problem I cant get my head around - I am not that great at the subsetting syntax. I have a dataset of longitudinal toxicity data (for multistate modelling) for which I want to also want to do a simple Kaplan-Meier curve of the time to first toxic event. The data for 2 cases presently looks like this (one with an event, the other without), with id representing

I hacked zstd support into OpenSSH a while ago and just started to clean it up in the recent days. The cleanup includes configuration support among other things that I did not have. During testing I noticed the following differences compared to zlib: - highly interactive shell output (as in refreshed at a _very_ high rate) may result in higher bandwidth compared to zlib. Since zstd is quicker

I added ZSTD support to OpenSSH roughly over a year and I've been playing with it ever since. The nice part is that ZSTD achieves reasonable compression (like zlib) but consumes little CPU so it is unlikely that compression becomes the bottle neck of a transfer. The compression overhead (CPU) is negligible even when uncompressed data is tunneled over the SSH connection (SOCKS proxy, port

This message was also sent to the MEDSTATS mailing list, so here is the reply I posted to that: Philippe, The machinery to use is to split follow-up time so finely that you can safely assume that rates are constant in each interval, and then just stuff it all into a Poisson model. This allows you to use any kind of time-dependent variables as well as accommodating competing risks. In the Epi

Hi, This patch (relative to -HEAD) defines an API to allow sandboxing of the pre-auth privsep child and a couple of sandbox implementations. The idea here is to heavily restrict what the network-face pre-auth process can do. This was the original intent behind dropping to a dedicated uid and chrooting to an empty directory, but even this still allows a compromised slave process to make new

https://bugzilla.mindrot.org/show_bug.cgi?id=2159 Bug ID: 2159 Summary: Implement SSH2_FXF_APPEND Product: Portable OpenSSH Version: 6.2p1 Hardware: Other OS: Linux Status: NEW Severity: enhancement Priority: P5 Component: sftp-server Assignee: unassigned-bugs at mindrot.org

Dear All, I would like to apply two different "for loops" to each set of four columns of a matrix (the loops here are simplifications of the actual loops I will be running which involve multiple if/else statements). I don't know how to "alternate" between the loops depending on which column is "running through the loop" at the time. ## Set up matrix J <- 10 N