Compute z-statistic for Sign test (ZScoreForSignTest
)¶
- class cerebstats.stat_scores.zSignScore.ZScoreForSignTest(*args: Any, **kwargs: Any)¶
Compute z-statistic for Sign Test.
Definitions
Interpretation
\(\eta_0\)
some specified value \(^{\dagger}\)
\(S^{+}\)
number of values in sample \(> \eta_0\)
\(S^{-}\)
number of values in sample \(< \eta_0\)
\(n_u\)
number of values in sample \(\neq \eta_0\), i.e., \(S^{+} + S^{-}\)
z-statistic, z
z = \(\frac{ S^{+} - \frac{n_u}{2} }{ \sqrt{\frac{n_u}{4}} }\)
\(^{\dagger} \eta_0\), null value is
the model prediction for one sample testing
0 for testing with paired data (observation - prediction)
Use Case:
x = ZScoreForSignTest.compute( observation, prediction ) score = ZScoreForSignTest(x)
Note: As part of the SciUnit framework this custom
TScore
should have the following methods,compute()
(class method)sort_key()
(property)__str__()
- classmethod compute(observation, prediction)¶
Argument
Value type
first argument
dictionary; observation/experimental data
second argument
floating number or array
Note:
observation must have the key “raw_data” whose value is the list of numbers