search for: counterfactuals

...nt to >> do, where these "other transforms" pretend certain abnormal cases do >> not exist. Poison is a "stand-in" for these transforms, which are >> sometimes non-local. > > I'm saying that you still get reasonable behavior from reasoning about > counterfactuals for these things, and I haven't been convinced that you > lose optimization power except in code that actually exhibits undefined > behavior. I'm not sure I understood your concern fully, but you could have cases like: for (...) { if (condition){ i32 prod = x *nsw y i64...

Hi John, John McCall wrote: >>> Well, we could say non-nsw add and mul are actually "bitwise" operations, so "mul i32 poison, 2" is guaranteed to have its bottom bit zero (but "mul nsw i32 poison, 2" is poison). Of course, there's a limit to how far we can go in that direction, or we just end up with the old notion of undef. Off the top of my head,

Greetings. There's a coalescing group which is working to imitate Dirk's fine translation of CRAN to APT, in the Fedora/Red-Hat flavored land. One of the things we're trying to do is implement as much as is possible in R directly, and use as much of the existing package management infrastructure as we can. To this end, I humbly submit a few small patches to that infrastructure.

Hello, I am running a model with four categories and want predicted probabilities in each category. Now for this example I wont give a counterfactual just the training data is fine but is there anyway to get a confidence interval around the predicted probabilities in each group? I have tried but it gives me probabilities and I have used interval="confidence", level=.095 and then interval

Dear list, My question to follow is not a pure R question but contains also a more general statistical/econometrical part, but I was hoping that perhaps someone knowledgable on this list could offer some help. I have estimated a binary logistic regression model and would like to calculate average marginal effects for certain predictors of interest. The average marginal effect for a continuous

Greetings, and apologies for the braino leading to my first posting to the general list. I'm reposting here, and changing how I attached the files; they were hard to work with in the other post. There's a coalescing group which is working to imitate Dirk's fine translation of CRAN to APT, in the Fedora/Red-Hat flavored land. One of the things we're trying to do is implement as

...can come up with an example that does not depend on signed overflow being “undefined” ? Peter Lawrence. > > >> >> >> Hi John, On 11/11/16, 1:58 PM, Sanjoy Das wrote: >> I'm saying that you still get reasonable behavior from reasoning about >> counterfactuals for these things, and I haven't been convinced that you >> lose optimization power except in code that actually exhibits undefined >> behavior. > > I'm not sure I understood your concern fully, but you could have cases like: > > for (...) { > if (condition)...

We're being ping-flooded by the Nachi worm, which probes subnets for systems to attack by sending 92-byte ping packets. Unfortunately, IPFW doesn't seem to have the ability to filter packets by length. Assuming that I stick with IPFW, what's the best way to stem the tide? --Brett Glass