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#bayes #programming #r #statistics

Question

After the analysis, we can examine whether the data are well described by the most credible possibilities in the considered set. If the data seem not to be well described, then we can consider expanding the set of possibilities. This process is called a [...]

Answer

posterior predictive check

Tags

#bayes #programming #r #statistics

Question

After the analysis, we can examine whether the data are well described by the most credible possibilities in the considered set. If the data seem not to be well described, then we can consider expanding the set of possibilities. This process is called a [...]

Answer

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Tags

#bayes #programming #r #statistics

Question

After the analysis, we can examine whether the data are well described by the most credible possibilities in the considered set. If the data seem not to be well described, then we can consider expanding the set of possibilities. This process is called a [...]

Answer

posterior predictive check

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#### Parent (intermediate) annotation

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nalysis, we can examine whether the data are well described by the most credible possibilities in the considered set. If the data seem not to be well described, then we can consider expanding the set of possibilities. This process is called a <span>posterior predictive check<span><body><html>

#### Original toplevel document (pdf)

owner: shihabdider - (no access) - Doing Bayesian Data Analysis, p24

nalysis, we can examine whether the data are well described by the most credible possibilities in the considered set. If the data seem not to be well described, then we can consider expanding the set of possibilities. This process is called a <span>posterior predictive check<span><body><html>

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|

repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

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