search for: assumpte

On Wed, Oct 16, 2013 at 1:58 PM, David Blaikie <dblaikie at gmail.com> wrote: > > > > On Wed, Oct 16, 2013 at 1:21 PM, Manman Ren <manman.ren at gmail.com> wrote: > >> >> There are a few places where we break the assumption: >> 1> formal_parameter constructed in DwarfDebug when adding attribute type >> we call SPCU->addType(Arg, ATy),

On Wed, Oct 16, 2013 at 9:10 PM, Manman Ren <manman.ren at gmail.com> wrote: > > > > On Wed, Oct 16, 2013 at 1:58 PM, David Blaikie <dblaikie at gmail.com> wrote: > >> >> >> >> On Wed, Oct 16, 2013 at 1:21 PM, Manman Ren <manman.ren at gmail.com> wrote: >> >>> >>> There are a few places where we break the assumption:

On Wed, Oct 16, 2013 at 10:32 PM, David Blaikie <dblaikie at gmail.com> wrote: > > > > On Wed, Oct 16, 2013 at 9:10 PM, Manman Ren <manman.ren at gmail.com> wrote: > >> >> >> >> On Wed, Oct 16, 2013 at 1:58 PM, David Blaikie <dblaikie at gmail.com>wrote: >> >>> >>> >>> >>> On Wed, Oct 16, 2013 at

Does anyone have any suggestions on how to best represent an assumption statement(*) in IR? In particular, I want to expose the information implied by the assumption to the optimization passes without emitting code (after optimization) to check the assumption itself. I've tried a couple of options so far, and none have gotten me quite the right semantics. Has anyone else implemented

On Wed, Oct 16, 2013 at 1:21 PM, Manman Ren <manman.ren at gmail.com> wrote: > > There are a few places where we break the assumption: > 1> formal_parameter constructed in DwarfDebug when adding attribute type > we call SPCU->addType(Arg, ATy), where Arg does not belong to SPCU. > 2> inlined_subroutine constructed in DwarfDebug when adding attribute >

There are a few places where we break the assumption: 1> formal_parameter constructed in DwarfDebug when adding attribute type we call SPCU->addType(Arg, ATy), where Arg does not belong to SPCU. 2> inlined_subroutine constructed in DwarfDebug when adding attribute abstract_origin The inlined_subroutine does not belong to the CU we call addDIEEntry on. We create the children

Hi, Johannes, Thanks for working on this. This seems like a good approach which nicely extends the set of capabilities we have now. One additional comment, as I agree with everything in your rationale, except this: > - Reconstructing information from the pattern of instructions that feed > into the `llvm.assume` is also not optimal, especially since we do > not need to

Hi Philip, > Does anyone have any suggestions on how to best represent an assumption > statement(*) in IR? good question! There have been various attempts, for example Nick tried teaching the optimizers to not prune the branch to unreachable in br %cond, label %assumption_holds, %assumption_doesnt_hold assumption_doesnt_hold: unreachable This then leads to %cond being replaced

add -basicaa to your command line :) On Mon, May 11, 2015 at 7:15 AM, Willy WOLFF <willy.mh.wolff at gmail.com> wrote: > I play a bit more with MemoryDependenceAnalysis by wrapping my pass, and > call explicitely BasicAliasAnalysis. Its still using No Alias Analysis. > > How can I let MemoryDependenceAnalysis use BasicAliasAnalysis? > > Please, find attached my pass. >

Hi All, I am doing linear mixed model analysis for my multi-location experiment using R package "lme4". I just wonder whether I should check my data first to see whether they meet the three assumptions of ANOVA, that is, independence, normality and homogeneity. I saw a lot of examples and the manual of lme4, but no one did data check first. In my experiment, the assumption of

Hi all, I was trying to test the assumption of proportional hazards assumption, I used the cox.zph function >cox.zph(coxfit6) Results are: rho chisq p x1 -0.0396 1.397 2.37e-01 x2 0.1107 9.715 1.83e-03 x3 -0.0885 7.743 5.39e-03 x4 0.0366 1.092 2.96e-01 x5 0.0242 0.455 5.00e-01 GLOBAL

I would like to test in R what regression fits my data best. My dependent variable is a count, and has a lot of zeros. And I would need some help to determine what model and family to use (poisson or quasipoisson, or zero-inflated poisson regression), and how to test the assumptions. 1) Poisson Regression: as far as I understand, the strong assumption is that dependent variable mean = variance.

> In beginModule, we construct the CUs, but not all the DIEs that belong to >>> the CU. >>> In endFunction, we started to construct the scope DIEs. So in some >>> sense, we are adding things to prior CUs. >>> >>> Looking at void CompileUnit::addDIEEntry(DIE *Die, uint16_t Attribute, >>> DIE *Entry), we can possibly have 3 CUs, this CU,

Hello, I know there is plenty of people in this group who can give me a good answer :) I have a 2^k model where k=4 like this: Model 1) R~A*B*C*D If I use the "*" in R among all elements it means to me to explore all interactions and include them in the model i.e. I think this would be the so called 2-way anova. However, if I do this, it leads to model violations i.e. the

On Wed, Oct 16, 2013 at 10:54 AM, Manman Ren <manman.ren at gmail.com> wrote: > > > > On Tue, Oct 15, 2013 at 5:59 PM, David Blaikie <dblaikie at gmail.com> wrote: > >> >> In beginModule, we construct the CUs, but not all the DIEs that belong >>>>> to the CU. >>>>> In endFunction, we started to construct the scope DIEs. So in

I want to test whether the proportional odds assumption for an ordered regression is met. The UCLA website points out that there is no mathematical way to test the proportional odds assumption (http://www.ats.ucla.edu/stat//R/dae/ologit.htm), and use graphical inspection ("We were unable to locate a facility in R to perform any of the tests commonly used to test the parallel slopes

Responding to both of your emails in one, sorry for the delay: > On Oct 25, 2016, at 11:20 AM, Peter Collingbourne <peter at pcc.me.uk> wrote: > I think there are a couple of additional considerations we should make here: > What are we trying to model? To me it's clear that GlobalConstant is for modelling integers, not pointers. That alone may not necessarily be enough to

On Wed, Oct 16, 2013 at 11:10 AM, David Blaikie <dblaikie at gmail.com> wrote: > > > > On Wed, Oct 16, 2013 at 10:54 AM, Manman Ren <manman.ren at gmail.com> wrote: > >> >> >> >> On Tue, Oct 15, 2013 at 5:59 PM, David Blaikie <dblaikie at gmail.com>wrote: >> >>> >>> In beginModule, we construct the CUs, but not all

On Tue, Oct 15, 2013 at 5:59 PM, David Blaikie <dblaikie at gmail.com> wrote: > > In beginModule, we construct the CUs, but not all the DIEs that belong >>>> to the CU. >>>> In endFunction, we started to construct the scope DIEs. So in some >>>> sense, we are adding things to prior CUs. >>>> >>>> Looking at void

Dear all, Can I do a permutation test if the number of individuals in one group is much bigger than in the other group? I searched the literature but I didin´t find any assumption that refers to this subject for permutation tests. Best regards João Fadista Ph.d. student UNIVERSITY OF AARHUS Faculty of Agricultural Sciences Dept. of Genetics and Biotechnology Blichers Allé 20, P.O.