How to calculate probabilities using Bayesian theorem
34 views (last 30 days)
Show older comments
Dear all,
I would like to calculate the probability of A, given B (p(a|b)) which can be done through the Bayesian theorem: p(a|b)=(p(b|a)/p(b))*p(a).
Im considering that: p(a)=normpdf(A) and p(b)=normpdf(B)
However, I'm not sure how to calculate p(b|a).
Can anoyone give me a hand on this?
Thank you in advance.
4 Comments
Ive J
on 5 Feb 2022
I assume by "working with matrices" you mean each random variable is stored in a different column of the matrix, with rows being the observations. In that case, you still can follow the link above.
Answers (1)
Pratyush
on 14 Dec 2023
Hi Ricardo,
I understand that you want to calculate ( P(A|B) ) using Bayes' theorem.
To do that you need ( P(B|A) ), ( P(A) ), and ( P(B) ). In MATLAB, "normpdf" can be used to calculate the probability density function (PDF) for ( P(A) ) and ( P(B) ), but this gives the density, not the actual probability.
For ( P(B|A) ), you need to know the relationship between ( A ) and ( B ):
- If ( A ) and ( B ) are independent, ( P(B|A) = P(B) ).
- If ( A ) and ( B ) are dependent, you need their joint distribution to calculate ( P(B|A) ).
Without knowing how ( A ) and ( B ) are related or having their joint distribution, you cannot calculate ( P(B|A) ). Additional information about their covariance or relationship is required to proceed with the calculation.
0 Comments
See Also
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!