@davidmanheim @rlmcelreath Yes, now the system is larger. Your model is higher fidelity in one part than another. Still a representation.
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Replying to @LifeOfMyMoon
@davidmanheim@rlmcelreath A Taylor series is a model of a function; you've *chosen* a point to approximate locally, but still has veracity.1 reply 0 retweets 1 like -
Replying to @LifeOfMyMoon
@LifeOfMyMoon@rlmcelreath Right; those are explicitly different models; which model you use depends on purpose - neither is "false".1 reply 0 retweets 0 likes -
Replying to @davidmanheim
@LifeOfMyMoon@rlmcelreath Actually, the no free lunch theorem effectively says explicitly that no model is best for all questions.1 reply 0 retweets 1 like -
Replying to @davidmanheim
@davidmanheim@rlmcelreath Definitely agree here. There is a degeneracy of states: multiple models have the same veracity, different focus1 reply 0 retweets 1 like -
Replying to @LifeOfMyMoon
@davidmanheim@rlmcelreath Except, NFL doesn't really apply: they hold information constant. Can form better model by obtaining perfect info1 reply 0 retweets 0 likes -
Replying to @LifeOfMyMoon
@LifeOfMyMoon@rlmcelreath Yes. Unfortunately, models exist to represent imperfectly, usually given available data.2 replies 0 retweets 0 likes -
Replying to @davidmanheim
@LifeOfMyMoon@rlmcelreath By extending models to represent the decision process w/ utilities, you can calculate VoI and collect more data.1 reply 0 retweets 0 likes -
Replying to @davidmanheim
@LifeOfMyMoon@rlmcelreath That's exactly why I like using models as incorporating the decision, so that you can, say, optimally sample.1 reply 0 retweets 0 likes -
Replying to @davidmanheim
@davidmanheim@rlmcelreath Utilities are just more variables in your objective model. Must try to get those right as well.2 replies 0 retweets 0 likes
@davidmanheim @rlmcelreath If they're wrong you say "this is subjective!" but only in the same way all subjectivity is false
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