Distributed, likelihood-free ABC-SMC inference

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pyABC

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Massively parallel, distributed and scalable ABC-SMC (Approximate Bayesian Computation - Sequential Monte Carlo) for parameter estimation of complex stochastic models. Implemented in Python with support of the R language.

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Many examples are available as Jupyter Notebooks in the examples directory and also for download and for online inspection in the example section of the documentation.

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0.12.15

0.12.13

0.12.12

0.12.11

0.12.10

0.12.9

0.12.8

0.12.7

0.12.6

0.12.5

0.12.4

0.12.3

0.12.2

0.12.1

0.12.0

0.11.12

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0.11.6

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0.11.3

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0.11.1

0.11.0

0.10.16

0.10.15

0.10.14

0.10.13

0.10.12

0.10.11

0.10.10

0.10.9

0.10.7

0.10.6

0.10.5

This version

0.10.4

0.10.3

0.10.2

0.10.1

0.10.0

0.9.26

0.9.25

0.9.24

0.9.23

0.9.22

0.9.21

0.9.20

0.9.19

0.9.18

0.9.17

0.9.16

0.9.15

0.9.14

0.9.13

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0.9.10

0.9.9

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0.9.1

0.8.19

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0.8.8

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0.8.6

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1

0.8.0

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0.7.1

0.7.0

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.5.2

0.5.1

0.5.0

0.4.4

0.4.2

0.4.0

0.3.3

0.3.2

0.3.1

0.3.0

0.2.1

0.2.0

0.1.3

0.1.2

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