For nucleotide models: Is the lnL score that GARLI reports at the end of a run comparable to the lnL scores reported by other ML search programs?

In general, you should not assume that lnL scores output by other ML search programs (such as PHYML and RAxML) are directly comparable to those output by GARLI, even if they apparently use the same model. To truly know which program has found a better tree you will need to score and optimize the resulting trees using a single program, under the same model. Because of the way that optimization is done in the various programs, PHYML, RAxML and PAUP* are all probably better suited for this final optimization and scoring of a fixed tree than GARLI is.

Also see the previous question. More.

I cant really gove you an answer,but what I can give you is a way to a solution, that is you have to find the anglde that you relate to or peaks your interest. A good paper is one that people get drawn into because it reaches them ln some way.As for me WW11 to me, I think of the holocaust and the effect it had on the survivors, their families and those who stood by and did nothing until it was too late.

Related Questions