I want to define an inequality constraint for a PYMC3 model. I found this post about defining an equality constraint (i.e., a+b1+b2=1) using pm.Potential. Does anyone know how to change that equality constraint into an inequality constraint like 0.9<a+b1+b2<1? Thanks! Source: Python..

#### Category : pymc3

I have been working using the following codes to acquire the Bayesian Fusion of StudentT distribution. Fusion code: def S2_0_Bayesian_Interface(data): ######################################################################################################################## with pm.Model() as model_0: # Prior Distributions for unknown model parameters: nu_0 = pm.HalfNormal(‘nu_0’, sd=1) sigma_0 = pm.HalfNormal(‘sigma_0’, sd=5) mu_0 = pm.Normal(‘mu_0’, mu=0, sd=5) # Observed data is from a Likelihood distributions (Likelihood (sampling ..

I want to apply theano.scan over multiple parameters in a hierarchical model. The code works great for a single model, however, I’m not sure how to convert the model to a hierarchical model (requiring additional looping). Here is the code for the single model: with pm.Model() as bayesian_reinforcement_learning: # data actions_ = pm.Data(‘actions’, actions) rewards_ ..

I have been trying to enable CUDA to run PyMC3 with the assistance of the GPU. Here are the specs of the machine/software I have been using: Windows 10 Visual Studio Community 2019 Python 3.8.12 CUDA 10.2 (I tried 11.2 before that and obtained the same problem) CuDNN 7.6.5 (I tried 8.1 with CUDA 11.2 ..

I am trying to recreate the models in John Kruschke’s ‘Doing Bayesian Data Analysis‘ and am currently trying to model ordinal data (chapter 23 in the book; see this post for the JAGS model and a translation into Python). This involves using the cumulative normal function (pnorm in R). I know of the existence of ..

I have some issues with theano package on my mac. I am getting the following error. File "/Users/model.py", line 355, in train train_model = theano.function( File "/Applications/anaconda3/lib/python3.8/site-packages/theano/compile/function/__init__.py", line 337, in function fn = pfunc( File "/Applications/anaconda3/lib/python3.8/site-packages/theano/compile/function/pfunc.py", line 426, in pfunc inputs = [ File "/Applications/anaconda3/lib/python3.8/site-packages/theano/compile/function/pfunc.py", line 427, in <listcomp> _pfunc_param_to_in(p, allow_downcast=allow_input_downcast) for p in params ..

I have the following PyMC3 code in Python, which are originated from here. In the last line, I got the error RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. I believe this error is similar to the error in this post. But I ..

I am a complete beginner in probabilistic programming so i am having some problems. For the purpose of my dissertation project, I need to evaluate the efficacy of a certain vaccine against Covid-19 using Bayesian methods. As it turns out, my population parameter (infection process, i.e., number of people infected) follows a Poisson prior, and ..

I ran into this piece of code: data = np.repeat((0, 1), (3, 6)) with pm.Model() as normal_approximation: p = pm.Uniform(‘p’, 0, 1) w = pm.Binomial(‘w’, n=len(data), p=p, observed=data.sum()) mean_q = pm.find_MAP() # MAP: maximum a posteriori probability std_q = ((1/pm.find_hessian(mean_q, vars=[p]))**0.5)[0] mean_q[‘p’], std_q I tried to search google generally and look at the documentation at ..

In pymc3 how does one configure a generalized normal distribution? Is there a tensorflow_probability GeneralizedNormal equivalent in PYMC3? https://www.tensorflow.org/probability/api_docs/python/tfp/distributions/GeneralizedNormal Source: Python..

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