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Hi there, I have some bird flight height data that follows a gamma distribution. The data (x) goes from 0 to 700 meters (n=1055). The calculated parameters calculated from the fitdistr(x) are (shape = 5.1379, rate = 0.017541), and therefore the scale (1/rate) = 57.00929. I would like to calculate the percentage of the function area that occurs below 50 meters (0-50m). Is that

...ill either need to regenerate kill flags after regalloc, or // preferably fix the scavenger to not depend on them). When looking in TwoAddressInstructionPass.cpp it looks like the pass only use/update LV when there is no LIS. And there seems to be an experimental -early-live-intervals option to calculcate LIS before TwoAddressInstructionPass. I also noticed that the -early-live-intervals option was added back in 2012. So I assume that the plans to replace LiveVariables by LiveIntervals in TwoAddressInstructionPass got some history. Has there been any evaluation (lately) from using -early-live-i...

...the compact letter display (CLD) of the multcomp package. # This shows boxplots (but it is easy to overlay the actual # observations, using the points() function) and uses letters # to indicate non-significance. # # (Note that (if I have understood everything correctly) this # doesn't actually calculcate Tukey HSD values (the "Tukey" # in the glht() call only selects Tukey *contrasts*), but # the results should be *very* similar.) library(multcomp) l.glht=glht(l, linfct = mcp(trt = "Tukey")) summary(l.glht) l.cld=cld(l.glht) old.par <- par( mai=c(1,1,2,1)) plot(l.cld) par(...

...0.4 setosa For each row, I look at the value of Sepal.Length. I then figure out the n rows where the value of Sepal.Length is closest to that in the original row, and apply a function on the values of Sepal.Width to these rows (typically returning a scalar). For example, setting n = 5 and calculcating the mean on a slightly modified dataset, based on the first row (Sepal.Length ~= 5.1): $ set.seed(1) $ iris[,1:4]=iris[,1:4]+runif(150)/100 $ x=iris$Sepal.Length[1] $ (pos=which(order(abs(iris$Sepal.Length-x)) %in% 2:6)) [1] 18 26 40 42 52 $ mean(iris$Sepal.Width[pos]) [1] 3.086595 Now, I c...

Where is the liveness analysis pass? I have been looking for days but cannot find anything. I just want to know transfer variables in and out of basic blocks, that are calculated using simple data flow equations. Thanks! -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.llvm.org/pipermail/llvm-dev/attachments/20180920/529bce15/attachment.html>