bayesian

  1. M

    Bayesian multiple comparison correction?

    Hi everyone, I am new to Bayesian statistics and am interested in the correlation of 4 "target" variables with 52 other variables. Currently I am running several separate Bayesian Spearman rank correlations. Many of the variables are highly correlated (up to .68). Finally, I would like to...
  2. N

    bayesian fish length-weight relationship

    hello, I am working on fish length-weight relationship: log W = log a + b log L with a sample size of n = 112. i wonder if i can get some feedback on using jasp summary stats bayesian one sample t test as a substitute for the frequentist t statistic = (b-3)/SE = 3.691, where b is the observed...
  3. B

    Probability of choosing 4 sick people from 100 where there is a probability of 8.6% for each of them to have a disease.

    I have the following task: There is 4% of sick people in a population. There is 5% chance for a positive test for a healthy person. There is 2% chance for a negative test for a a sick person. We tested 100 people and 4 had a positive test. What is the probability of such an outcome? So far I...
  4. hlsmith

    One-Sample Bayesian Proportion Test

    https://www.lexjansen.com/phuse/2011/sp/SP08.pdf In the above (short) paper, the authors present an approach for a one-sample Bayesian proportion test with uninformed and informed priors. Below I have presented code for the informed setting, which consists of just a few lines of code. However...
  5. I

    Interpreting the result of a Bayesian Structural Times Series model

    A bit of context: I am reading a study called "Exploring the determinants of Bitcoin Price". In this research paper google search trends across different countries over time are used, in part, to determine price movements in Bitcoin. They use a Bayesian Structural Times Series model. I am...
  6. U

    Bayes Nordics - a list for the Bayesian community in the European Nordic countries

    Bayes Nordics is a list serving the Bayesian community in the European Nordic countries. Bayes Nordics disseminates news on events related to Bayesian analysis: workshops, conferences, seminars, job openings and courses related to Bayesian reasoning, methods, practice and computation, with...
  7. hlsmith

    Bayesian Posterior: SD = SE?

    I was curious if the standard deviation in a Bayesian posterior is equal to the standard error?
  8. T

    What's wrong with my BANOVA (Bayesian ANOVA)?

    Hi everyone... I'm new to Bayesian statistics and I'm trying to perform a BANOVA. I'm using the following book to help me: "Doing Bayesian Data Analysis A Tutorial Introduction with R and BUGS", written by John K. Kruschke. I'm working on a simulated data set, trying to find a difference in...
  9. L

    Proof of Kalman filter related lema

    Hi... Can you please provide a proof of the formula given on the attached image?
  10. S

    Imdb top 250 and bottom 100 calculation

    https://en.wikipedia.org/wiki/IMDb#Ranking The above page describes how the top 250 is calculated where the m (prior) value is set at 25000 for top 250, and for bottom 100 , the m value is set at 1500. My question is the following 1)Why conduct bottom 100 separately because the bottom...
  11. T

    decision under loss function, discrete Bayes

    Hi guys, This is my first post here. I am currently enrolled in the Coursera Bayesian Statistics course from Duke University. While I've enjoyed the Statistics with R specialization so far, I think this course is not at the same level as the other ones. In one of the quizzes from the course...
  12. E

    AMOS Bayesian MCMC

    When using Bayesian MCMC in AMOS, do the MCMC algorithms allow for nonlinearity? I know all the other estimation algorithms do not [e.g. maximum-likelihood (ML)]. Also, does anyone know of any research articles that involve Bayesian CFA and measurement invariance that is similar or the same...
  13. I

    Comparing the output of JAGS to conjugate analysis - normal with unknown mean and var

    Dear Bayesians. I'm starting my way in the Bayesian world, and I'm trying to build a simple model for estimating the mean and variance of a normal distribution. I assume that: y=rnorm(100,50,4) # This would be the data mu0=0 #Prior of mean var0=100 #Prior for the variance #I continue...
  14. O

    Evaluation of Bayesian Model

    How can I evaluate if a created bayesian model is reliable model that makes good predication? To conclude if the created bayesian model produces a low error rate.
  15. N

    Finding Joint Posterior Density of Poisson and Exp?

    Hi, Some friends and I have been stuck on this bayesian stats question for five days now, please shed some light if you can :wave: We've tried to multiply the the Poisson posterior density and exponential posterior density together to produce a joint density, but we're told it's not correct :/...
  16. S

    Combining two data sets using Bayesian methods

    Hi, I want to combine multiple data sets of customer spend data together. I want to calculate how the bounds of the data decrease as I add in more data sets (so I can do things like estimate the ROI error for a whole year, as opposed to one week's spend). I believe there is a Bayesian method...
  17. B

    bayesian statistics

    I have a large amount of data, given totals for every hour over a year period for the following columns: # of Jams Jam event time in minutes # of Full occurances Full event time in minutes and Runtime, product flow (counts) I am trying to create a bayesian model using iPython and...
  18. M

    Bayesian MCMC Fitting lognorm mixture model w/constraint on population mean

    I am trying to find a reference and/or guidance for fitting a mixture model to a population of data within an MCMC framwork where the global mean is constrained to a particular value, in this case 1. That is, E(X) = 1 where f(X) = \sum \omega_i f_i(x| \theta_i) and the standard constraint \sum...
  19. N

    Bayesian inference with unequal sampling

    I have a "two-column" data set, with a multi-class categorical variable A, and two-class variable B. It is assumed that each observation is independent. For each category of variable A, I want to make a Bayesian estimate of a binomial parameter for class 1 of variable B, consistent with the...
  20. J

    Bayesian statistics proof question

    I know that if the prior distribution is chosen to be a continuous uniform distribution, then the exact posterior distribution will simply the normalized version of the likelihood function. I was wondering how i would write this out as a proof?