search for: counterbalanc

...vecot stone, but the more users you have the more stones you'll likely need. This is because most people are rather unhappy with their lives, and they project their negative energies towards their surroundings, including their email servers. To overcome this negative energy you need to have a counterbalancing positive energy, which the Dovecot stones will provide you. The Dovecot stones are hand painted from the finest materials available to the sister of the author of Dovecot that she could find in the local shops. Each stone contains such love and dedication towards the well being of Dovecot that...

...er() 2) Use::get/set due to tagging. The former is seldom called: $ find lib -name "*.cpp" | xargs grep "getUser(" | wc -l 41 We could audit those to make sure that no unnecessary calls are done. But the getUse() algorithm is not sooo inefficient, anyway. The second is counterbalanced with a faster access to the Use object in most cases: With exception of PHINode and SwitchInst, the getOperand() function (if called on a specialized "this" pointer) does a "this"-relative access instead of getting OperandList pointer first and going thru that. This was the...

...etUser(" | wc -l > 41 The majority of those aren't actually Use::getUser, but on the other hand this grep misses all the users of value_use_iterator::operator*, which is much more popular. Unfortunately, overloaded operators are not the easiest to grep for ;-). > The second is counterbalanced with a faster access to the Use object > in most cases: > With exception of PHINode and SwitchInst, the getOperand() function > (if called on a specialized "this" pointer) does a "this"-relative > access instead of getting OperandList pointer first and going thru...

...low 2 1.4 B low 3 1.7 A low 4 1.9 B low 5 2.0 A low 6 2.1 B low The order of treatment is counterbalanced and I would assume I would choose to fit the model: > model1<-lme(response~treat, random=~1|femaleset/group) or > model2<-lmer(response~treat+(1|femaleset/group)) However I am concerned with two aspcts: my small sample size of course but also the use of a random effect of female s...

Hi I have data from an experiment that used a repeated-measures factorial 2x2 design (i.e. each participant contributed data to both levels of both factors). I need a non-parametric version of the repeated-measures factorial ANOVA to analyse the data. SPSS only has non-parametric tests for one-way ANOVAs but I have been told that the test I need can be implemented using the R software.

Hi Gabor, Can you provide performance data for this? I'd like to know what affect these changes have on compile time. Thanks, Dan On Apr 15, 2008, at 3:32 PM, Gabor Greif wrote: > Hi All, > > here comes the patch for the second wave of Use class size reduction. > > I have included all the machinery that is needed, and it is > *active*. The User* inside of Use is even

Hi All, here comes the patch for the second wave of Use class size reduction. I have included all the machinery that is needed, and it is *active*. The User* inside of Use is even sometimes NULL, but the algorithm is able to recover it. If there is a non-null User* present, then I am asserting that it equals the computed value. I did not receive feedback for the algorithmic part yet, so I