Linked Questions

5
votes
3answers
2k views

Q: what book on Bayesian statistics, preferably with R? [duplicate]

I am frequentist by training and practice, but I'd like to learn more about Bayesian statistics. I know the basics, but I would be at a loss if I had to, for example, replace my normal ANOVA ...
2
votes
1answer
2k views

Book Bayesian statistics [duplicate]

I write here to ask for a suggestion about a graduate level Bayesian statistics book. I have a bachelor degree in statistics but despite having a fairly solid background on frequentist and non ...
0
votes
2answers
546 views

Recommendations for learning probability and Bayesian statistics? [duplicate]

I have been very interested lately in learning Bayesian Statistics, but I have only a little bit of background in the frequentist statistics, only one term at University. Some of the books that I ...
1
vote
1answer
518 views

How did you learn Bayesian statistics and what would you recommend as a reliable source? [duplicate]

I'm running a Bayesian model and I'm stuck on some aspect of the model that I have difficulty to understand. Since my knowledge about Bayesian inference is limited, I would like to have some good ...
3
votes
1answer
126 views

Bayesian references [duplicate]

Any good places to start getting into Bayesian statistics? I'm a graduate student in social sciences, with a decent amount of stats classes under my belt, but I'm far from fluent. Any references would ...
0
votes
1answer
78 views

Non-technical reference for Bayesian probability [duplicate]

Could anyone suggest a good, non-technical, high-level explanation of Bayesian probability? To clarify, since some people suggested a thread with recommendations of textbooks, that isn't really what ...
0
votes
0answers
67 views

recommended books for preliminary concepts of Bayesian Statistics [duplicate]

I am interested in learning Bayesian Statistics related for my CS career. I have a very little background on frequentist statistics, which I know differs from the bayesian approach. The reason of my ...
0
votes
0answers
26 views

Good books for self studying Bayesian [duplicate]

What are some good books with the help of which I can self-study Bayesian from the basics to advanced, mentioning why do we need Bayesian and also which contains numericals, which can boost my concept....
18
votes
6answers
3k views

What is a good book about the philosophy behind Bayesian thinking?

What is a good book about Bayesian philosophy, contrasting subjectivists against objectivists, explaining the view of probability as state of knowledge in Bayesian statistics, etc.? Maybe Savage's ...
16
votes
4answers
6k views

Checking whether accuracy improvement is significant

Suppose I have an algorithm that classifies things into two categories. I can measure the accuracy of the algorithm on say 1000 test things -- suppose 80% of the things are classified correctly. Lets ...
4
votes
2answers
3k views

Use of prior and posterior predictive distributions?

I understand the prior and posterior distributions and I have read what the prior and posterior predictive distributions are. However, I don't really see the point of knowing them. Knowing more ...
4
votes
5answers
367 views

Which expansions and identities are useful to applied statisticians? [closed]

Simple mathematical relationships like $V(X) = E(X^2) - E(X)^2$, aside from being theoretical results, are useful because they allow analysts to do back-of-the-envelope calculations, restate results ...
3
votes
2answers
1k views

“Bayesian and Frequentist Regression Methods” by Jon Wakefield, a good introductory Bayesian textbook for frequentist economics graduates?

Here's a link to a good question regarding Textbooks on Bayesian statistics from some time ago. People suggested John Kruschke's "Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS"...
1
vote
1answer
1k views

Composition of probability density

I know probability distribution for parameter $\phi$. I have the empirical distribution/statistical distribution of $X$ that is dependent on parameter $\phi$ for $\phi \in [0,1]$. I assimilate this ...
5
votes
1answer
1k views

Questions on Bayesian Softmax Regression [closed]

My question is about how to actually do this both rigorously and practically. Allow me to elaborate. Suppose that we have data $(x_1,y_1),...,(x_N,y_N) \in \mathbb{R}^p \times \{0,...,k-1 \}$. I'd ...

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