pal package
Proteus Actuarial Library (PAL).
A simple, fast and lightweight framework for building simulation-based actuarial and financial models.
PAL is designed to look after the complicated stuff, such as copulas and simulation re-ordering, providing easy to use objects and clear syntax.
PAL is based on the scientific python stack of numpy and scipy for fast performance. It can optionally run on a GPU using the cupy package for extremely fast performance. It is designed for interoperability with numpy and ndarrays.
See: http://github.com/ProteusLLP/proteus-actuarial-library
Submodules
- pal.config module
- pal.contracts module
- pal.copulas module
CopulaEllipticalCopulaGaussianCopulaStudentsTCopulaArchimedeanCopulaClaytonCopulalevy_stable()GumbelCopulaFrankCopulaJoeCopulaMM1CopulaGalambosCopulaPlackettCopulaHuslerReissCopulaHuslerReissCopula.__init__()HuslerReissCopula.is_adjustedHuslerReissCopula.dimensionHuslerReissCopula.adjusted_lambda_matrixHuslerReissCopula.apply()HuslerReissCopula.tail_dependence_matrixHuslerReissCopula.calculate_lambda_from_tail_dependence()HuslerReissCopula.from_tail_dependence_matrix()HuslerReissCopula.generate()
ExtremalTCopulaapply_copula()
- pal.couplings module
- pal.distributions module
DistributionBaseDiscreteDistributionBasePoissonNegBinomialBinomialHyperGeometricBernoulliGPDBurrBetaLogLogisticNormalLogisticLogNormalGammaInverseGammaParetoParalogisticInverseBurrInverseParalogisticWeibullInverseWeibullGEVStudentsTInverseGaussianExponentialUniformInverseExponentialDistributionGeneratorBaseDiscreteDistributionGeneratorContinuousDistributionGenerator
- pal.frequency_severity module
- pal.maths module
- pal.stats module
- pal.stochastic_scalar module
StochasticScalarStochasticScalar.coupled_variable_groupStochasticScalar.__init__()StochasticScalar.valuesStochasticScalar.n_simsStochasticScalar.ranksStochasticScalar.tolist()StochasticScalar.mean()StochasticScalar.sum()StochasticScalar.all()StochasticScalar.any()StochasticScalar.astype()StochasticScalar.std()StochasticScalar.percentile()StochasticScalar.tvar()StochasticScalar.upsample()StochasticScalar.show_histogram()StochasticScalar.show_cdf()
- pal.types module
- pal.variables module
ProteusVariableProteusVariable.__init__()ProteusVariable.dim_nameProteusVariable.valuesProteusVariable.dimensionsProteusVariable.count()ProteusVariable.index()ProteusVariable.get_value_at_sim()ProteusVariable.upsample()ProteusVariable.sum()ProteusVariable.validate_freqsev_consistency()ProteusVariable.from_csv()ProteusVariable.from_dict()ProteusVariable.from_series()ProteusVariable.correlation_matrix()ProteusVariable.show_histogram()ProteusVariable.show_cdf()