Displaying 17 results from an estimated 17 matches for "multist".
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multhist
2008 May 28
0
multistate survival analysis w/ time varying covariates
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
2013 Feb 26
0
Multistate occupancy models using Jags
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...
2013 Oct 07
4
Feature request: FQDN Host match
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
2023 Feb 24
1
[PATCH 1/1] Add support for ZSTD compression
...;
+ }
sshbuf_reset(state->incoming_packet);
if ((r = sshbuf_putb(state->incoming_packet,
state->compression_buffer)) != 0)
diff --git a/readconf.c b/readconf.c
index cf79498848f6d..f05aab2316c8a 100644
--- a/readconf.c
+++ b/readconf.c
@@ -899,8 +899,14 @@ static const struct multistate multistate_pubkey_auth[] = {
{ NULL, -1 }
};
static const struct multistate multistate_compression[] = {
+#if defined(WITH_ZLIB) || defined(HAVE_LIBZSTD)
+ { "yes", COMP_ALL_C },
+#endif
#ifdef WITH_ZLIB
- { "yes", COMP_ZLIB },
+ { "zlib", COMP_ZLIB },
+#...
2011 Mar 22
0
why the survival function estimate using package 'mstate' & package 'cmprsk' vary from sas and LTA (From WHO).
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...
2009 Feb 26
1
logistic regression - unequal groups in R
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 it is objecting to?
Do I have to have equal numbers of observations of all categories in R?
nt1 is the total number of events for which p1 is the success proportion,
each is linked with a category, vis...
2008 Jun 30
1
ctree (party) plot meaning question
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 significant
asssociation with the response?
:confused:
Many thanx in advance
B.
-----
The art of living is more...
2008 Jul 18
1
finding "chuncks" of data that have no NA s
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...
2010 Nov 11
1
exploratory analysis of large categorical datasets
...e 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",
"V.4", "V.5")))
and the second one is a multistate 750x1500 matrix, with up to 15
*unordered* states per variable, in the form:
matrix(sample(c(1:15),25,replace=TRUE), nrow = 5, ncol=5, dimnames = list(c(
"group1", "group2","group3", "group4","group5"), c("V.1", "V.2", "...
2023 Feb 24
1
[PATCH 0/1] ZSTD compression support for OpenSSH
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
2007 Apr 23
1
data recoding problem
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 each person on study, and follow-up
time and status:
> tox
id t...
2020 Mar 24
4
ZSTD compression support for OpenSSH
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
2020 Sep 05
8
[PATCH 0/5] ZSTD compression support for OpenSSH
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
2008 Jul 27
0
competing risk model with time dependent covariates under R or Splus
...t 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 package (http://staff.pubhealth.ku.dk/~bxc/Epi/) on CRAN there is a machinery for representation and manipulation of multistate data (of which competing risks are a special case), see the function Lexis().
It also has a time-splitting function there, splitLexis().
If you take a look at practical 14 from this year's SPE course:
http://staff.pubhealth.ku.dk/~bxc/SPE/2008/pracs.pdf
there is an example that addresses th...
2011 Jun 22
3
sandbox pre-auth privsep child
...0,7 @@ fill_default_server_options(ServerOption
/* Turn privilege separation on by default */
if (use_privsep == -1)
- use_privsep = 1;
+ use_privsep = PRIVSEP_SANDBOX;
#ifndef HAVE_MMAP
if (use_privsep && options->compression == 1) {
@@ -701,6 +701,12 @@ static const struct multistate multistat
{ "no", 0 },
{ NULL, -1 }
};
+static const struct multistate multistate_privsep[] = {
+ { "sandbox", PRIVSEP_SANDBOX },
+ { "yes", PRIVSEP_ON },
+ { "no", PRIVSEP_OFF },
+ { NULL, -1 }
+};
int
process_server_config_line(ServerO...
2013 Oct 14
6
[Bug 2159] New: Implement SSH2_FXF_APPEND
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
2012 Jul 30
2
Alternating between "for loops"
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