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Non-self-promoters depend on people like you.
Empirical Bayes procedures can be shown to be robust to the distribution of the data in a way that Bayesian procedures cannot. The difference between Empirical bayes and Bayesianism along this important dimension make them very distinct procedures from the perspective of many users.
This difference is most commonly seen in practice when some density must be estimated for inference. Use of kernel density estimation in empirical Bayes ensures an asymptotic convergence to the true density at some rate. In contrast, no Bayesian prior has yet been developed with consistency for density estimation.
v cannot have negative entries. It appears that are you are forgetting the signs in the formula for the adjugate.
v is guaranteed to exist and be a valid probability vector as long as M is an irreducible Markov matrix (that is, any state can eventually be reached from any other state). An equivalent and intuitively easier way to calculate v is by repeatedly squaring M: when you do this, all rows of M^k converge to v. This is a consequence of the fact that v is an equilibrium state, i.e., the probability distribution you end up with if you let the Markov chain run forever (from any starting state).
The ability to identify important people in our life is vital to our identity. What level of fine detail would be required to preserve this? It would be disconcerting to be reconstructed but to lack a memory of what your mother looked like.
Volunteering to perform is a huge status move.
History is probably the best guide here.
Our intuitive concept of 'life' conflates two concepts: the ability to reproduce and complexity. Many would consider a machine made by an advanced civilization (but incapable of reproduction) as 'alive'; meanwhile, one might hesitate to call prions 'alive', despite their capacity to replicate, merely due to their simplicity.
Try to convert your non-rationalist friends.
Sure, utility and intelligence might be orthogonal. But very different utilities could still lead to very similar behaviors.
I'd suggest going into research first, to improve your credentials and also to gain a solid understanding of statistics. If you don't like biology, business schools use a lot of Bayesian techniques.
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