Category : pymc3

pymc3.stats.summary function clearly documented at https://pymc3-testing.readthedocs.io/en/rtd-docs/api/stats.html Yet an attempt to use this function pymc3.stats.summary(self.trace_y_j_t, include_transformed = True, to_file = txt_filename) results in, e.g. TypeError: summary() got an unexpected keyword argument ‘include_transformed’ Removing the include_transformed arg and going with to_file only gives the same sort of error for that argument. PyMC3 is somewhat infamous for poor ..

Read more

import pymc3 as pm import numpy as np x = np.linspace(0,1,100) y_true = 3*x + 5 y_obs = y_true + np.random.normal(loc=0, scale=0.02,size=100) with pm.Model() as model: a = pm.Normal(‘a’, mu=2.0, sigma=3.0) b = pm.Normal(‘b’, mu=2.0, sigma=3.0) y_model = a*x + b s = pm.HalfNormal(‘s’, sigma=0.05) likelihood = pm.Normal(‘y’, mu=y_model, sigma=s, observed = y_obs) trace = ..

Read more

I’m learning the basics of PyMC3. In a spine regression section, 4.74, the author of this notebook, uses the following code: from patsy import dmatrix B = dmatrix( "bs(year, knots=knots, degree=3, include_intercept=True) – 1", {"year": d2.year.values, "knots": knot_list[1:-1]}, ) I’ve never used Patsy before, though I’ve consulted the documentation: https://patsy.readthedocs.io/en/latest/API-reference.html https://patsy.readthedocs.io/en/latest/formulas.html#formulas From what I’ve gained, ..

Read more

I am trying to configure PyMC3 Polynomial kernel with the following hyperpriors; with pm.Model() as self.model: EPSILON = 0.1 l = pm.Gamma("l", alpha=2, beta=1) offset = pm.Gamma("offset", alpha=2, beta=1) nu = pm.HalfCauchy("nu", beta=1) d = pm.HalfNormal("d", sd=5) cov = nu ** 2 * pm.gp.cov.Polynomial(X.shape[1], l, d, offset) self.gp = pm.gp.Marginal(cov_func=cov) sigma = pm.HalfCauchy("sigma", beta=1) y_ ..

Read more

I am trying to build a simple model using PyMC3. The model should draw 10 samples from 10 discrete uniform distributions. Those 10 samples should then be used to calculate the difference between each consecutive sample, take the absolute value and calculate the mean. The mean of the differences should then be used as the ..

Read more