The bayes tag has no wiki summary.
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1answer
15 views
Help with Bayesian inference in OpenBugs
I have a task that involved Bayesian inference and could use some pointers and hints. I've already got some parts figured out but others remain blurred. Also, my OpenBUGS abilities are frankly limited ...
2
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2answers
36 views
Applying Bayes: Estimating a bimodal distribution
I'm trying to estimate a bunch of bimodal distributions, i.e. two means and two standard deviations, based on a variable number of inputs. If no input is present, a constant value should be returned. ...
4
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2answers
117 views
Help me understand Bayesian prior and posterior distributions
I'm taking a course on Bayesian statistics but my mind seems rather incapable of coping with it. I've got here a very specific nut I've tried to crack open all day. Gah.
In a group of students, there ...
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0answers
50 views
Derive Likehood of the data
Can somebody help me with this problem:
Suppose we wish to model two variables x and y, as having an underlying linear relation with added errors. That is, with data $(x,y)_i: i = 1,...,n$, we model
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0
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1answer
75 views
Laplace approximation of the likelihood Bayesian
I need help with the following question:
Consider $m$ observations $(y_1; n_1); ... ; (y_m; n_m)$, where $y_i \sim Bin(n_i; θ_i)$ are binomial variables.
Assume that $θ_i \sim w_1Beta(α_1; β_1) + ...
1
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1answer
45 views
Calculating whether a disease is probable using Bayes rule?
I want to compute whether it is more probable that a patient has a disease or the contrary. If I am given the following information:
P(disease)= 0.008
P(+|disease)= 0.98
P(-|¬disease)= 0.97
To ...
1
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2answers
46 views
How can I use Bayes rule for this question given additional data
I am required to use the Naive Bayes classifier to classify example 8, to see whether it is poisonous or not.
I gained the following results:
p(x|Poisonous=Y) = 0.0267857 and
p(x|Poisonous=N) = ...
0
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0answers
60 views
How to solve this problem using Bayes Rule?
I have become stuck on answering question 1c, which requires me to: use the Bayes rule with the naive Bayes Assumption. I understand how to use the naive Bayes classifier but not using the assumption.
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1
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1answer
55 views
Is a diffuse prior always weak?
There are countless examples of diffuse priors being used to 'allow the data to speak.' However, what if one's past experience leads you to be skeptical of new data, without necessarily having a ...
0
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1answer
57 views
Dumb Bayes theorem question
What's the difference between "probability of H given E" as calculated by Bayes theorem and the "positive predictive value" of E?
3
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0answers
85 views
Using priors to detect an effect? logistic Bayesian regression
I have designed an idea and am looking for similar approaches in other literature/areas or if I have applied the Bayesian concepts wrongly. Here is a statement of my problem:
I am modeling the ...
1
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1answer
62 views
Bayes' rule for conference talk attendance
This seems like a typical Bayes' Rule question, but I'm having trouble formulating it properly.
Say I'm a speaker on a conference tour which moves from city to city. I'm trying to estimate how many ...
1
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1answer
102 views
WinBUGs-TImes Series Code
I am looking to get started using times series (arima) (regression) (etc) evaluating log stock returns in WinBUGs. Does anyone have a simple code to get me jump started?
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2answers
142 views
Bayes specify informative and uninformative prior
I would be really thankful for any hint
Let $x_1,\dots x_n$ be a sample from a geometric distribution with probability parameter $\theta$
$f(x_i\mid \theta)=\theta(1-\theta)^{x_i}$
The likelihood ...
1
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0answers
25 views
Why is Bayesian error concave down as a function of prior P(w1)?
Given a two categorization problem, why Bayesian error is concave down as a function of prior P(w1)?
w1, w2 are two underlying concepts with prior P(w1) and P(w2). We observe the evidence x, which is ...
4
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1answer
166 views
Elementary MCMC pseudocode
My aim relates to the project described here, but I've tried to make this question self-contained.
I'm trying to write the MCMC pseudocode for the following inference problem:
Given two observed ...
1
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0answers
46 views
Reliability ratings in Bayes' theorem
In his 1967 paper “A Theorem for Prediction” (Studies in Intelligence 11(4)), Jack Zlotnick discusses how some CIA experiments lead to a “modification” of Bayes' theorem, to account for unreliable ...
1
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1answer
83 views
Conditional expectation of discrete variables
I am trying to find E[Y|X] when only given the facts that:
${\bf P[Y=y] = 2/3, y=0 }$ ${\bf 1/3, y=1 }$ ${\bf 0, else }$
and ${\bf P[X=x|Y=y] = 2/3, x,y=0}$ or ${\bf x,y=1 }$
${\bf ...
1
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0answers
67 views
Individual-level parameter estimates from ordered choice regressions
I have got a question regarding ordered choice regressions in R.
I have several demographic variables with which I want to explain the ordered choice of individuals within a survey in an ordered ...
2
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2answers
115 views
A question about notation of Bayes' Theorem
when I studied the Bayesian statistics, a question about notation of Bayes Theorem came to my mind. Below is the density function version of Bayes Theorem, $y$ is data vector and $\theta$ is parameter ...
-1
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1answer
65 views
Joining results from different laboratories
I've done a large number of tests (100). I also have access to a thesis where it is reported the same type of tests on the same type of material. The mean and COV values are reported, along with the ...
3
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2answers
488 views
Linear discriminant analysis and Bayes rule
What is the relation between Linear discriminant analysis and Bayes rule? I understand that LDA is used in classification by trying to minimize the ratio of within group variance and between group ...
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0answers
76 views
bayesian test of linear regression hypothesis
write program bayesian test of linear regression hypothesis In R or winbugs :
...
0
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2answers
96 views
How to calculate the probability that an algorithm classifies seven wines out of ten correctly when the true error is 0.23?
I am considering the following problem.
Calculate the exact probability that an algorithm classifies seven
wines out of ten correctly when the true error is 0.23.
Should I solve this with ...
4
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1answer
284 views
Empirical Bayes and random effects?
I recently happend to read about empirical Bayes (some introduction by Cassella?)
and it looked a lot like random effects model; in that both have estimates shrunken to global mean...
But I havent ...
3
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1answer
182 views
Is Bayes' theorem useless if $A$ is a subset of $B$?
Using Bayes' theorem, $P(A|B) = P(B|A)P(A) / P(B)$
wouldn't this just be the percentage of $A$ in $B$ if $A$ is a subset of $B$?
If A is a subset of B:
$$P(B|A) = 1,$$
$$P(A|B) = P(A) / P(B)$$
...
19
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2answers
1k views
Likelihood ratio vs Bayes Factor
I'm rather evangelistic with regards to the use of likelihood ratios for representing the objective evidence for/against a given phenomenon. However, I recently learned that the Bayes factor serves a ...
2
votes
1answer
111 views
The unit information prior and its BIC approximation
Just moments ago, I asked this question because I've been reading Wagenmakers 2007. I now have a better understanding of what a unit information prior is and can push my knowledge further with two (by ...
2
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1answer
229 views
What is a “Unit Information Prior”?
I've been reading Wagenmakers (2007) A practical solution to the pervasive problem of p values. I'm intrigued by the conversion of BIC values into Bayes factors and probabilities. However, so far I ...
