genetest.statistics.models package¶
Submodules¶
genetest.statistics.models.linear module¶
-
class
genetest.statistics.models.linear.StatsLinear(condition_value_t=1000, eigenvals_t=1e-10)[source]¶ Bases:
genetest.statistics.core.StatsModelsInitializes a ‘StatsLinear’ instance.
Parameters: - condition_value_t (int) – The condition value threshold (for multicollinearity). Usually, values higher than 1000 indicate strong multicollinearity or other numerical problems.
- eigenvals_t (float) – The Eigen value threshold (for multicollinearity). Usually, values lower than 1e-10 might indicate strong multicollinearity or singular design matrix.
-
fit(y, X, handler=None)[source]¶ Fit the model.
Parameters: - y (pandas.DataFrame) – The vector of endogenous variable.
- X (pandas.DataFrame) – The matrix of exogenous variables.
genetest.statistics.models.logistic module¶
-
class
genetest.statistics.models.logistic.StatsLogistic[source]¶ Bases:
genetest.statistics.core.StatsModels-
fit(y, X)[source]¶ Fit the model.
Parameters: - y (pandas.DataFrame) – The vector of endogenous variable.
- X (pandas.DataFrame) – The matrix of exogenous variables.
-
genetest.statistics.models.mixedlm module¶
-
class
genetest.statistics.models.mixedlm.StatsMixedLM(reml=True)[source]¶ Bases:
genetest.statistics.core.StatsModelsInitializes a ‘StatsMixedLM’ instance.
Parameters: reml (bool) – Whether to use REML or ML for the test. -
fit(y, X)[source]¶ Fit the model.
Parameters: - y (pandas.DataFrame) – The vector of endogenous variable.
- X (pandas.DataFrame) – The matrix of exogenous variables.
-
genetest.statistics.models.survival module¶
-
class
genetest.statistics.models.survival.StatsCoxPH[source]¶ Bases:
genetest.statistics.core.StatsModels-
fit(y, X)[source]¶ Fit the model.
Parameters: - y (pandas.DataFrame) – The vector of endogenous variable.
- X (pandas.DataFrame) – The matrix of exogenous variables.
Warning
The y dataframe (outcome) should contain two columns: tte and event.
-