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Results tagged with bayesian
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user 382413
Bayesian inference is a method of statistical inference that relies on treating the model parameters as random variables and applying Bayes' theorem to deduce subjective probability statements about the parameters or hypotheses, conditional on the observed dataset.
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How to properly put lower/upper limits on a Bayesian posterior
The uniform distribution is often applied to situations where $w \in [l,u]$ represents a segment on the real line, with no preferred value for $w$ within this segment. However, on the one hand, this a …
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Are “Data are fixed” in Bayesian viewpoint and “Data are random” in frequentist viewpoint ta...
What are data? Data come in all shapes and sizes. But what are data actually?
My height and weight can be measured, and their values are read using a scale and a ruler. The values can be recorded with …
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In Bayesian linear regression Advantages of predictive posterior compared to posterior of mo...
Well, every Bayesian model involves a likelihood function and a prior probability. The likelihood function usually is rather well understood. …
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iid data (Bayesian) vs iid random variables (Frequentist)?
There are no random variables in Bayesian theory, only probability distributions. … Bishop's PRML is an excellent book for learning a lot of Bayesian methods. However, in Chapter 1, Bishop adopts a frequentist approach, which does a disservice to the remainder of his book. …
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Independence and conditional independence in probability
It is not an answer, but explaining the concept of logical implication may be helpful.
A implies B, or $A \Rightarrow B$, can be illustrated by this table
where the 1s mean True and the 0 is False.
T …
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