Ambrosia 0.4.0
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Documentation and usage examples have been substantially reworked and updated.
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The
Designer
class and design methods functionality is updated.-
Empirical design now supports the choice of hypothesis alternative and group ratio parameter
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Look of resulting tables with calculated parameters is unified for all design methods
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Changed multiprocessing strategy for bootstrap criterion
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The
Tester
class functionality is updated.-
Spark data support for the
Tester
class is added. Independent t-test is available now -
Bootstrap criterion can now return deterministic output using a
random_seed
parameter -
Paired bootstrap criterion is now available
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MHC now is optional and takes into account the number of passed metrics
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first_errors
parameter renamed tofirst_type_errors
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pyspark
package now is optional and could be installed usingpip
extras. -
Fixed a set of bugs.