33 Matching Annotations
  1. Dec 2023
  2. Jul 2023
    1. weakly informative approach to Bayesian analysis

      In [[Richard McElreath]]'s [[Statistical Rethinking]], he defines [[weakly informative priors]] (aka [[regularizing priors]]) as

      priors that gently nudge the machine [which] usually improve inference. Such priors are sometimes called regularizing or weakly informative priors. They are so useful that non-Bayesian statistical procedures have adopted a mathematically equivalent approach, [[penalized likelihood]]. (p. 35, 1st ed.)

    1. Science is not described by thefalsification standard, as Popper recognized and argued.4 In fact, deductive falsification isimpossible in nearly every scientific context. In this section, I review two reasons for thisimpossibility.(1) Hypotheses are not models. The relations among hypotheses and different kinds ofmodels are complex. Many models correspond to the same hypothesis, and manyhypotheses correspond to a single model. This makes strict falsification impossible.(2) Measurement matters. Even when we think the data falsify a model, another ob-server will debate our methods and measures. They don’t trust the data. Sometimesthey are right.For both of these reasons, deductive falsification never works. The scientific method cannotbe reduced to a statistical procedure, and so our statistical methods should not pretend.

      Seems consistent with how Popper used the terms [[falsification]] and [[falsifiability]] noted here

    2. Statistical RethinkingA Bayesian Coursewith Examplesin R and StanRichard McElreath

      A companion book to [[Richard McElreath]]'s phenomenal lecture course [[Statistical Rethinking]] which he made freely available here.

      Note that this is the 1st ed. of the book (2015).

      source

    3. Statisticians, for theirpart, can derive pleasure from scolding scientists, which just makes the psychological battleworse.

      Note to self: don't do this.

    4. So where do priors come from? They are engineering assumptions, chosen to help themachine learn. The flat prior in Figure 2.5 is very common, but it is hardly ever the best prior.You’ll see later in the book that priors that gently nudge the machine usually improve infer-ence. Such priors are sometimes called regularizing or weakly informative priors.They are so useful that non-Bayesian statistical procedures have adopted a mathematicallyequivalent approach, penalized likelihood. These priors are conservative, in that theytend to guard against inferring strong associations between variables.

      p. 35 where [[Richard McElreath]] defines [[weakly informative priors]] aka [[regularizing priors]] in [[Bayesian statistics]]. Notes that non-Bayesian methods have a mathematically equivalent approach called [[penalized likelihood]].

    5. The other imagines instead that population size fluctuates through time, which can be trueeven when there is no selective difference among alleles.

      McElreath is referring to \(\text{P}_{0\text{B}}\) (process model zero-B).

    6. one assumes the population size andstructure have been constant long enough for the distribution of alleles to reach a steady state

      The population size & structure being "constant" is what [[Richard McElreath]] means by "equilibrium" in \(\text{P}_{0\text{A}}\) (process model zero-A), which corresponds to the null hypothesis

      \(\text{H}_0: \text{``Evolution is neutral"}\)

    7. Andrew Gelman’s

      Per Andrew Gelman's wiki:

      Andrew Eric Gelman (born February 11, 1965) is an American statistician and professor of statistics and political science at Columbia University.

      Gelman received bachelor of science degrees in mathematics and in physics from MIT, where he was a National Merit Scholar, in 1986. He then received a master of science in 1987 and a doctor of philosophy in 1990, both in statistics from Harvard University, under the supervision of Donald Rubin.[1][2][3]

  3. Sep 2021
    1. I told them it was the Sabbath day, and desired them to let me rest

      She hadn't practiced a sabbath before, why is she upset about this one?

    2. She didn't even pass through the water like a baptism entails she skirted over it in a raft. It even dictates that "my food did not wet"

    3. stoutest men, and sent them back to hold the English army in play whilst the rest escaped.

      Men who would die for the benefit of the tribe. A war with the English army

    1. “Wait on the Lord, Be of good courage, and he shall strengthen thine Heart, wait I say on the Lord.”

      it seems like she isn't exactly bothered by captivity. Although I understand her urging her not because she's pregnant and due soon. But shouldn't she at least think about running away too if she's captive and unhappy.

    2. chapter of Deuteronomy

      What is the significance to this chapter?

    3. One of the Indians that came from Medfield fight, had brought some plunder, came to me, and asked me, if I would have a Bible, he had got one in his basket. I was glad of it, and asked him, whether he thought the Indians would let me read? He answered, yes. So I took the Bible,

      They treat captives with more kindness than the Englishmen do. They still let her have access to religious texts.

    4. Then they went and showed me where it was, where I saw the ground was newly digged, and there they told me they had buried it.

      They took the time to bury it upon a hill and to tell her where her baby was buried

    5. my sweet babe like a lamb departed this life on Feb. 18, 1675. It being about six years, and five months old.

      No one should go through the death of a baby. Why is there no distinguishing language about the baby? no possessive descriptions or even a name

    6. Then I took oaken leaves

      Seems like herbal remedies which are common from pagans and Native Americans

    7. and my child’s being so exceeding sick,

      I thought her children died??

    8. One of the Indians got up upon a horse, and they set me up behind him, with my poor sick babe in my lap.

      It seems to be that the once off act of kindness might actually be a pattern

    1. still the Lord upheld me with His gracious and merciful spirit, and we were both alive to see the light of the next morning.

      God's mercy and love kept them alive through to the morning

    2. but God was with me in a wonderful manner, carrying me along, and bearing up my spirit, that it did not quite fail.

      Why is God with her all of a sudden? I'm sensing a theme of Christianity and praising the Lord.

    3. One of the Indians carried my poor wounded babe upon a horse

      Quite interesting since they are 'barbaric' creatures. Why would they carry her wounded baby on a horse showing kindness to her?

    1. All was gone, my husband gone (at least separated from me, he being in the Bay; and to add to my grief, the Indians told me they would kill him as he came homeward), my children gone, my relations and friends gone, our house and home and all our comforts—within door and without—all was gone (except my life), and I knew not but the next moment that might go too.

      Alluding to how the Englishmen killed the Natives and took them slaves as a way of profit.

    2. one-eyed John, and Marlborough’s Praying Indians

      Are these characters to be followed up on?

    3. Oh the roaring, and singing and dancing, and yelling of those black creatures in the night, which made the place a lively resemblance of hell.

      Shows the disconnect that English people felt at the time and the animistic view of Native Americans that was portrayed.

    4. “What, will you love English men still?”

      Her being in Native American territory somehow denotes her English nature?

  4. Aug 2020
  5. Jul 2020