# Tagged Questions

1answer
28 views

### A Question from textbook “Learning with Kernels”

I am reading the book "Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)". I finished the first chapter and didn't ...
1answer
42 views

### Distribution of logically constrained parameters in Monte Carlo simulation

Papers like Briggs et al. 2002 say that logical constraints on inputs such as probability parameters exclude the the Normal distribution from consideration due to its unboundedness. In this example, ...
2answers
217 views

### Q: what book on Bayesian statistics, preferably with R?

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 ...
1answer
69 views

### Do Bayesians interpret the likelihood distribution as subjective as well?

One of the main differences between Bayesians and frequentists is that they have a subjective interpretation to probability. However, do Bayesians actually interpret subjectively the probabilities ...
2answers
122 views

### Bayesian and frequentist interpretations vs approaches

I have been reading about the frequentist vs bayesian issue (this article has helped a lot, specially with the example; also this one), and I haven't come to terms with it. At the moment it seems like ...
3answers
171 views

### Why are Bayesian methods widely considered particularly “convenient”?

Several times I have come across (in lectures, papers, etc.) informal/tangential remarks that have the following basic form: Philosophical issues aside, Bayesian methods are extremely convenient. ...
1answer
90 views

### A Bayesian perspective on omitted-variable bias (and other covariate-selection bias problems)

As I know OVB, from a frequentist education, when you leave a variable $(z)$ out of your control set $(X)$ that is correlated with both your independent variable of interest (treatment $T$) and your ...
3answers
166 views

### Does talking about a probability of future events make you a Bayesian?

Okay, so I sent a confession of love to a girl detailing several reasons and coming up with a 90% probability that I will be with her together for my whole life. But I then thought that I was ...
1answer
99 views

### Confusion related to a post related to statistics in xkcd [duplicate]

I came across this post http://xkcd.com/1132/ and this image I didn't get why the Bayesian statistician is saying no. Any suggestion
1answer
67 views

### Statistical error in Bayesian framework

Residuals and errors are related but not exchangeable. In Wikipedia I read: In statistics and optimization, statistical errors and residuals are two closely related and easily confused measures of ...
1answer
99 views

### Outline of benefits/costs of using Bayesian rather than Frequentist OLS and time-series?

I'm reading up on Bayesian techniques for Linear models and time series. While the texts are great at teaching the theory I would like to get a better handle on the pro's/con's of Bayesian analysis vs ...
1answer
117 views

### Under what conditions do Bayesian and frequentist point estimators coincide?

With a flat prior, the ML (frequentist -- maximum likelihood) and the MAP (Bayesian -- maximum a posteriori) estimators coincide. More generally, however, I'm talking about point estimators derived ...
4answers
605 views

### Bayesian uninformative priors vs. frequentist null hypotheses: what's the relationship?

I came across this image in a blog post here. I was disappointed that reading the statement did not illicit the same facial expression for me as it did for this guy. So, what is meant by the ...
1answer
95 views

### Priors for parameters of normal distribution leading to same results as frequentist formula

Given a sample vector $x$ of size $N$ from a normally distributed population. With frequentist methods the population mean is estimated as $\hat{\mu}=\frac{\Sigma{}x_i}{N}$, population sigma is ...
1answer
156 views

### On FDA guidance about Bayesian practice

US FDA authorizes the use of Bayesian statistics with informative priors (in certain contexts): ...
0answers
46 views

### Anomaly prediction confidence for frequentist vs bayesian parameter inference

I am comparing the behavior of some implementations of Bayesian and frequentist approaches to parametric anomaly detection and currently trying to figure out the differences when the sample set is ...
1answer
199 views

### Bayesian and frequentist approaches: What are some success stories for the former? [duplicate]

Possible Duplicate: Examples of Bayesian and frequentist approach giving different answers What are some practical examples where a Bayesian approach has an edge over frequentist ...
2answers
185 views

### Results Difference: Frequentist vs. Bayesian

I fit a lognormal model on some data points using both frequentist and Bayesian (using a non-informative prior) approaches. However, I got different results. Here are my codes and outputs: ...
1answer
120 views

### how would you approach giving an introductory class about Bayesian statistics?

I need to give a lecture about Bayesian statistics, introducing it to people who have already basic knowledge of classic statistics (but not too much of it in general). I want to start with some ...
1answer
197 views

### How to estimate right-skewed distribution with very small sample size?

Suppose we have a data set consists of, say, 5 or 10 observations. The only thing we know about this set is that it came from a positive right skewed distribution. How can we fit a probability ...
5answers
2k views

### Examples of Bayesian and frequentist approach giving different answers

Note: I am aware of philosophical differences between Bayesian and frequentist statistics. For example "what is the probability that the coin on the table is heads" doesn't make sense in frequentist ...
11answers
7k views

### What's wrong with XKCD's Frequentists vs. Bayesians comic?

This xkcd comic (Frequentists vs. Bayesians) makes fun of a frequentist statistician who derives an obviously wrong result. However it seems to me that his reasoning is actually correct in the ...
6answers
801 views

### List of situations where a Bayesian approach is simpler, more practical, or more convenient

There have been many debates within statistics between Bayesians and frequentists. I generally find these rather off-putting (although I think it has died down). On the other hand, I've met several ...
2answers
162 views

### Are there any other interpretations besides bayesian and frequentist?

I am aware of the frequentist and bayesian interpretations of statistics. I prefer Bayesian because I think it's closer to how people think, and because we in practice often can't rerun a trial a ...
0answers
82 views

### Random sample of population sub sample size

I am generating models and each model is a random sample of the total model population. It is recommended that I generate 30,000 models and cluster taking the top 5 to 10 clusters to reach the native ...
5answers
550 views

### Do Bayesians ever argue there are cases in which their approach generalizes/overlaps with the frequentist approach?

Do Bayesians ever argue that their approach generalizes the frequentist approach, because one can use non-informative priors and therefore, can recover a typical frequentist model structure? Can ...
7answers
815 views

### What is the connection between credible regions and Bayesian hypothesis tests?

In frequentist statistics, there is a close connection between confidence intervals and tests. Using inference about $\mu$ in the $\rm N(\mu,\sigma^2)$ distribution as an example, the $1-\alpha$ ...
5answers
562 views

### If you use a point estimate that maximizes $P(x | \theta)$, what does that say about your philosophy? (frequentist or Bayesian or something else?)

If somebody said "That method uses the MLE the point estimate for the parameter which maximizes $\mathrm{P}(x|\theta)$, therefore it is frequentist; and further it is not Bayesian." would you ...
2answers
223 views

### Frequentism and priors

Robby McKilliam says in a comment to this post: It should be pointed out that, from the frequentists point of view, there is no reason that you can't incorporate the prior knowledge into the ...
2answers
264 views

### Bayesian and frequentist optimization and intervals

I realize the methodology pursued by the Frequentist and Bayesian camps generally differ. However, one method of estimation that they do share is optimization of a certain function: Frequentists ...
0answers
82 views

### Probabilistic (Bayesian) vs Optimisation (Frequentist) methods in Machine Learning [duplicate]

Possible Duplicate: Bayesian and frequentist reasoning in plain English A very similar question was posed on stats.SE: Bayesian and frequentist reasoning in plain English, which provoked ...
1answer
306 views

### What are the modeling approaches in this cartoon?

What are the modeling approaches depicted here? Can you name them and their prominent proponents or a landmark model? Is there an accepted superior approach? Who prefers which approach? (From: ...
2answers
319 views

### Are there differences in Bayesian and frequentist approaches to EDA?

Very simply put: Are there any differences in Bayesian and Frequentist approaches to Exploratory Data Analysis? I know of no inherent biases in EDA methods as a histogram is a histogram, a ...
5answers
465 views

### Is there more to probability than Bayesianism?

As a student in physics, I have experienced the "Why I am a Bayesian" lecture perhaps half a dozen times. It is always the same -- the presenter smugly explains how the Bayesian interpretation is ...
0answers
581 views

### Is it OK to do additive smoothing before applying Pearson's chi-square test for independence?

I'm concerned about treating my data as gold, especially in areas of low data support, so I would like to apply additive smoothing. I'm then doing several things with this data, and one of them is ...
3answers
2k views

### Is Bayesian statistics genuinely an improvement over traditional (frequentist) statistics for behavioral research?

While attending conferences, there has been a bit of a push by advocates of Bayesian statistics for assessing the results of experiments. It is vaunted as both more sensitive, appropriate, and ...
2answers
269 views

### Statistical landscape

Has anyone written a brief survey of the various approaches to statistics? To a first approximation you have frequentist and Bayesian statistics. But when you look closer you also have other ...
4answers
2k views

### Confidence intervals for regression parameters: Bayesian vs. classical

Given two arrays x and y, both of length n, I fit a model y = a + b*x and want to calculate a 95% confidence interval for the slope. This is (b - delta, b + delta) where b is found in the usual way ...
7answers
18k views

### What's the difference between a confidence interval and a credible interval?

Joris and Srikant's exchange here got me wondering (again) if my internal explanations for the the difference between confidence intervals and credible intervals were the correct ones. How you would ...
5answers
1k views

### Do working statisticians care about the difference between frequentist and Bayesian inference?

As an outsider, it appears that there are two competing views on how one should perform statistical inference. Are the two different methods both considered valid by working statisticians? Is ...
14answers
13k views

### Bayesian and frequentist reasoning in plain English

How would you describe in plain English the characteristics that distinguish Bayesian from Frequentist reasoning?