|
45 | 45 | "import pymc3 as pm\n", |
46 | 46 | "\n", |
47 | 47 | "with pm.Model() as model:\n", |
48 | | - " parameter = pm.Exponential(\"poisson_param\", 1)\n", |
| 48 | + " parameter = pm.Exponential(\"poisson_param\", 1.0)\n", |
49 | 49 | " data_generator = pm.Poisson(\"data_generator\", parameter)" |
50 | 50 | ] |
51 | 51 | }, |
|
123 | 123 | ], |
124 | 124 | "source": [ |
125 | 125 | "with pm.Model() as model:\n", |
126 | | - " theta = pm.Exponential(\"theta\", 2)\n", |
| 126 | + " theta = pm.Exponential(\"theta\", 2.0)\n", |
127 | 127 | " data_generator = pm.Poisson(\"data_generator\", theta)" |
128 | 128 | ] |
129 | 129 | }, |
|
221 | 221 | ], |
222 | 222 | "source": [ |
223 | 223 | "with pm.Model() as model:\n", |
224 | | - " parameter = pm.Exponential(\"poisson_param\", 1, testval=0.5)\n", |
| 224 | + " parameter = pm.Exponential(\"poisson_param\", 1.0, testval=0.5)\n", |
225 | 225 | "\n", |
226 | 226 | "print(\"\\nparameter.tag.test_value =\", parameter.tag.test_value)" |
227 | 227 | ] |
|
296 | 296 | ], |
297 | 297 | "source": [ |
298 | 298 | "with pm.Model() as model:\n", |
299 | | - " lambda_1 = pm.Exponential(\"lambda_1\", 1)\n", |
300 | | - " lambda_2 = pm.Exponential(\"lambda_2\", 1)\n", |
| 299 | + " lambda_1 = pm.Exponential(\"lambda_1\", 1.0)\n", |
| 300 | + " lambda_2 = pm.Exponential(\"lambda_2\", 1.0)\n", |
301 | 301 | " tau = pm.DiscreteUniform(\"tau\", lower=0, upper=10)\n", |
302 | 302 | "\n", |
303 | 303 | "new_deterministic_variable = lambda_1 + lambda_2" |
|
1607 | 1607 | "x = np.ones(N, dtype=object)\n", |
1608 | 1608 | "with pm.Model() as model:\n", |
1609 | 1609 | " for i in range(0, N):\n", |
1610 | | - " x[i] = pm.Exponential('x_%i' % i, (i+1)**2)" |
| 1610 | + " x[i] = pm.Exponential('x_%i' % i, (i+1.0)**2)" |
1611 | 1611 | ] |
1612 | 1612 | }, |
1613 | 1613 | { |
|
0 commit comments