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Questions tagged [pymc]

PyMC is a Python library for performing Bayesian inference using MCMC. It is a Python equivalent to JAGS and BUGS.

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23 views

Bayesian liability threshold model

Let $\bf{y}$ denote a vector of binary data, such as whether a group of individuals suffer from a particular disease, and let $\bf{X}$ denote a matrix of potential predictors, including an intercept ...
45 views

Using information involving multiple model parameters as a prior

I am estimating a relatively simple linear equation of the following form: $$y = \beta_0 + \beta_1p + \beta_2t +\epsilon$$ I would like to take a bayesian modelling approach, and have existing ...
24 views

bayesian estimation of difference between 2 non-normal groups

Lets say we have 2 sets of groups with random variable X as shown. Features of X based on real dataset: They are all positive numbers have really long right tail and almost no left tail Cant share ...
25 views

Why Are they doing exponential distributions?

With many thanks for help in why my exercise is using a Gamma distribution, I am still confused by another part. The plot: The commentary: We may suspect from the above that there is some sort of ...
10 views

Softmax Linear Regression/ Multinomial Logistic Regression with shared coefficients and different inputs

I am trying to build a Softmax Regression model for 3 classes, where, unlike what is usually done, the coefficients between different options are shared and what varies are the input variables. ...
20 views

Modelling a random variable that is mostly zero, but otherwise exponential (PyMC3)

I'm new to probabilistic programming, and have run into problems of this kind a few times now. Simply put: I often find myself wanting to model a random variable that mostly has some nice, continuous ...
33 views

pymc3: Updating the standard error prior

I am estimating a Bayesian multiple regression using continuous data on both the dependent variable and the regressors. My goal is to iteratively estimate the coefficient distributions as more data ...
30 views

281 views

Using PyMC3, how could I force a maximum to posterior distribution?

I am pretty new to bayesian statistics and PyMC3. I am doing a hierarchical model where the output variable I am trying to predict is a percentage with a maximum of 100%. My problem is that my ...
245 views

Bayesian Modeling: Yes, No and Maybe Responses

Respondents replied in the following way: Yes: they will be attending No: they won't be attending Maybe: they attach a percentage certainty as an estimate that they'll be attending. E.g. 40% sure ...
49 views

Estimate a parameter from subset of the data, other parameters from all data

I use Bayesian random effects models [$y_i \sim bernoulli\_logit(\beta + \alpha_{subj})$ $\alpha_{subj} \sim normal(0, \gamma)$], the $y$ outcome is binary. Part of the subjects have two observations,...
102 views

Bayesian modeling of 2x2 factorial design. Am I doing it right?

I have a 2x2 factorial design with factors task (a, b) and stimulus type (c, d). I'm looking at behavioral data and was wondering how to test the main effect of task. To be more specific, I want to ...
529 views

Bayesian Neural Network in timeseries [closed]

I am currently exploring Bayesian Neural Network application on timeseries and stumbled on pymc3 library. But don't exactly understand how can I use it on a timeseries data. I am coming from a ...
43 views

Understanding covariance in Bayesian regression model

I am confused about when to model covariance in a Bayesian regression. Here's what I am trying to model. I have a dataset which has scores for a set of students who did a set of practice exam problems....