Linked Questions
34 questions linked to/from Bayesian and frequentist reasoning in plain English
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Bayesian : Comparing means of two posterior samples/ Help a Frequentist Out
UPDATE Thanks for the many thoughtful responses and questions! I've made edits here to clarify further. and also respond to each respondent individually.
Original Post
I have two sets of posterior ...
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Does bayesians' critique to frequentists apply to themselves too?
I've been reading about bayesians versus frequentists, including articles in this forum (like this one). Key is of course the issue of "priors". The bayesian critique being that frequentists ...
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Why would considering $\theta$ to be a random variable not be 'Bayesian'?
I am currently studying the textbook In All Likelihood -- Statistical Modelling and Inference Using Likelihood by Yudi Pawitan. Section Inverse probability: the Bayesians of chapter 1 says the ...
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Bayesian Bootstrap interpretation
I am using Bayesian Bootstrap for some analysis. Given dataset $X=\{x_1, \dots, x_N\}$, we generate bootstrapped samples $X_1,\dots, X_K$ by sampling from the $X$, with replacement. In classical ...
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Can someone explain why Bayesian networks are called "Bayesian"
I have been reading Jensen's book on Bayesian Networks and Decision Graphs as well as the Deep Learning book by Bengio, et. al. I am trying to understand why undirected graphs are referred to as ...
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The difference between the Frequentist, Bayesian and Fisherian appraoches to statistical inference [duplicate]
I'm just trying to get my head around the differences between these three approaches to statistical inference. I'm just not entirely sure what the significant differences are between the three.
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Repeated Measures ANOVA post hoc test (bayesian)
I am trying to understand the procedure of carrying out a Bayesian Repeated Measures ANOVA. In a conventional repeated measures ANOVA, I calculate the effect of a certain parameter (e.g., study ...
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Relation between MAP, EM, and MLE
I am a beginner in machine learning. I can do programming fine but the theory confuses me a lot of the times.
What is the relation between Maximum Likelihood Estimation (MLE), Maximum A posteriori (...
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When (and why) do Bayesians reject valid Bayesian methods? [closed]
From what I have read and from answers to other questions I have asked here, many so-called frequentist methods correspond mathematically (I don't care if they correspond philosophically, I only care ...
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Estimation derived from ignorance
Is something wrong with the following reasoning? Mostly I wonder how could one derive uniformly random arrival from ignorance. But even if that derivation is invalid generally, it seems reasonable ...
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Include prior knowledge in regression model
I've a classical dataset with real attributes and I want to perform a regression.
But, not all the entries in the training dataset are trustworthy; there is an attribute that I can turn into a ...
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Predicting future values with a regression model
I have a set of predictor variables and a target variable. I am really confused with regards to what method to use for forecasting the target variable.
For example, my data set has monthly customer ...
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When can't frequentist sampling distribution be interpreted as Bayesian posterior in regression settings?
My actual questions are in the last two paragraphs, but to motivate them:
If I am attempting to estimate the mean of a random variable that follows a Normal distribution with a known variance, I've ...
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Bayesian vs. frequentist estimation
I don't really understand the connection between bayesian to "normal" frequentist estimation.
Suppose we want to estimate the expected value of a population given a sample.
In frequentist statisics ...
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Bayesian vs. frequentist view [duplicate]
I have tried to figure out the difference between the two views of looking at the world: Bayesian and frequentist.
Can someone please let me know if I have it right? (Please do not refer me to some ...
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