search for: races

Colleagues, I am in the process of learning R. I've been able to import my dataset (from Stata) and do some simple coding. I have now come to coding situation that requires some assistance. This is some code in SPSS that I would like to be able to execute in R: if (race eq 1 and usborn=0) confused=1 . if (race eq 2 and usborn=0) confused=1 . if (race eq 1 and usborn=1) confused=0 . if (race

...ear from the first race i have to add +1. But i am not sure how to write the code into R. Can anyone help me get the longest break in the first year of racing for each horse? Jana. -- View this message in context: http://r.789695.n4.nabble.com/Urgent-help-needed-for-honours-project-breaks-between-races-in-one-year-tp3878187p3878187.html Sent from the R help mailing list archive at Nabble.com.

Hello, We have a publication in ASPLOS 2012 that uses the LLVM infrastructure. Is it possible to add this to the publications web page: http://llvm.org/pubs/ ? Publication: Data Races vs. Data Race Bugs: Telling the Difference with Portend Link: http://dl.acm.org/citation.cfm?id=2150997 Abstract: Even though most data races are harmless, the harmful ones are at the heart of some of the worst concurrency bugs. Alas, spotting just the harmful data races in programs is like find...

Hi, I am trying a linear regression model where the dependent variable is the size of the heart corrected for the patient's height and weight. This is labelled as LAVI. The independent variables are race (european or non-eurpoean), age, sex (male or female) of the patient and whether they have diabetes and high blood pressure. sample size 2000 patients selected from a community. when I

This test has been broken for a while. It is meant to test that when the appliance cachedir is empty, two simultaneous runs of libguestfs (both rebuilding the full appliance) will not cause conflicts, because (eg) the locking in either supermin or libguestfs is not working. However the test only set $TMPDIR, but the ./run script sets $LIBGUESTFS_CACHEDIR which overrides $TMPDIR, so it was simply

I have a large dataset where each Subject answered seven similar Items, which are binary yes/no questions. So I've always used Subject and Item random effects in my models, fit with lmer(), e.g.: model<-lmer(Response~Race+Gender+...+(1|Subject_ID)+(1| Item_ID),data,binomial) But I recently realized something. Most of the variables that I've tested as fixed effects are properties

...aused by read()]. I finally realized that linking with libtsan installs wrappers around the syscalls for read(), close(), etc. where the wrappers create an underlying mutex and read/write operations on sentinel memory, so that it can then reuse its memory race analysis it has for more typical data races. The wrappers thus cause odd-looking reports for fd races (the report ends up claiming that Thread 1 performing close() lost a race to Thread 2 performing read() - even though the ACTUAL data race is only a bug when Thread 2 loses the race and read()s on an fd close()d by Thread 1 and possibly reu...

Hi Jake, About a year ago in commit 5049c3422d26b2b68877307c41b35d7e6aae3235, you attempted to solve a race in llvm-objcopy. What was the race? I ask because unless "last change wins" is the result you want, then the race isn't solved. The problem is that `sys::fs::rename` is just a thin wrapper around POSIX semantics, and replacing an existing file is not an error. Dave

...Sanitizer (race detector), I need > to distinguish between a store to vtable pointer (vptr) and any other > regular store. > This special treatment should be limited to class DTORs, so I should also > know when a function is a DTOR. > Rationale: need to distinguish benign and harmful races on vptr > (http://code.google.com/p/data-race-test/wiki/PopularDataRaces#Data_race_on_vptr). > > Currently, I can figure out when a function is a DTOR and when a store > touches vptr by analyzing mangled names. > _ZN1BD1Ev=="B::~B()" > _ZTV1B=="vtable for B" &g...

...een using the val.prob function from the Design library (Thanks Frank!!) to both evaluate and visualize my model. From the scores and graph, it appears as my model is very accurate in predicting probabilities correctly. Please see attachment "graph1.pdf" Since I'm scoring horse races, I assume that I need to "normalize" the predicted probabilities by race. (Described in Bentor.) I am calculating a conditional logit manually since there is a bug in the Survival library for this function. A val.prob function applied to my conditional logit score shows an interestin...

Hi folks, I have five imputed data sets and would like to apply the same recoding routines to each. I could do this sort of thing pretty easily in Stata using MIM, but I've decided to go cold turkey on other stats packages as a incentive for learning more about R. Most of the recoding is for nominal variables, like race, religion, urbanicity, and the like. So, for example, to recode race

There is a race condition between XEN_DOMCTL_SHADOW_OP_ENABLE_LOGDIRTY and HVMOP_track_dirty_vram hypercall. Although HVMOP_track_dirty_vram is called many times from qemu-dm which is connected via VNC, XEN_DOMCTL_SHADOW_OP_ENABLE_LOGDIRTY is called only once from a migration process (e.g. xc_save, libxl-save-helper). So the race seldom happens, but the following cases are possible.

...to maximize the liklihood of of a "True" label per group. An toy explanation is probably best. I've been looking at horse racing models as a fun field to learn about statistics and R. So, for this example, lets assume the following: 100 horses in our stable 10 horses per race 75 races this season (some horses race more than once.) The independent variables are things about a horse (average speed, number of past wins, etc.) The dependent variable is (Win, Lose) represented by (1,0) As mentioned above, an SVM or GLM will quickly work to estimate coefficients and probability of...

...menting LLVM IR in ThreadSanitizer (race detector), I need to distinguish between a store to vtable pointer (vptr) and any other regular store. This special treatment should be limited to class DTORs, so I should also know when a function is a DTOR. Rationale: need to distinguish benign and harmful races on vptr ( http://code.google.com/p/data-race-test/wiki/PopularDataRaces#Data_race_on_vptr ). Currently, I can figure out when a function is a DTOR and when a store touches vptr by analyzing mangled names. _ZN1BD1Ev=="B::~B()" _ZTV1B=="vtable for B" define linkonce_odr void @_Z...

What''s the standard way to prevent race conditions in controllers? Say user has many posts. Post controller has action add_post that receives user id, post controller find()s the user and while he is creating the post entry an administrator deletes that user in a separate session. We cannot assume the database checks foreign key integrity. How do you get that right? -- fxn

I'm uncertain if this is perhaps a stupid question: I want to create "centered" dummy variables to use in a call to glm(), and wondering if there's some slick method in R to do so. That is, rather than have a factor, which results in a glm() fit returning coefficients specifying either absence or presence of the factor, I'd like to fit a glm() without intercept such that

I have been trying to use lavaan (version 0.4-7) for a simple path model, but the program seems to be computing far less degrees of freedom for my model then it should have. I have 7 variables, which should give (7)(8)/2 = 28 covariances, and hence 28 DF. The model seems to only think I have 13 DF. The code to reproduce the problem is below. Have I done something wrong, or is this something I

I have a data set with seven inputs. Four of which are categorical. For my midterm, my professor wants us to scale all the inputs. This means, I pressume, that I have to use 'recode' or 'factor' to transform the categorical data in numerical. For example, one input variable is 'race=(b,w,h,o)'. I just want to assign a numerical value to all 'b,w,h,o'. I

Hello: I have an lme object, say lme_res2, which was generated using the varIdent. I'm trying to extract the double 1.532940 from the object, but I can't find it by attributes(lme_res2) or attributes(summary(lme_res2)). How can I pull it out (so that I can save it to another variable)? Thanks. Shin Linear mixed-effects model fit by REML Data: dat Log-restricted-likelihood:

I just started using R and I'm having all sorts of "fun" trying different things. I'm going to document the different things I'm doing here as a kind of case study. I'm hoping that I'll get help from the community so that I can use R properly. Anyways, in this study, I have demographic data, drug usage data, and side effect data. All of this is loaded into a csv