Modules#
Summary of modules of nomopy
- Factorial hidden Markov models (nomopy.fhmm):
FHMM: Implementation of a factorial hidden Markov model, including (1) several expectation-maximization (EM) algorithms for model parameter fitting, (2) confidence interval generation, (3) hidden state trajectory reconstruction, and (4) data generation
FHMMCV: Machinery for cross-validation and model selection through train-test splitting of noise timeseries
Hessian: Machinery for computing the Hessian of the loglikelihood with respect to model parameters
- Higher order statistics (nomopy.hos):
second_spectrum(): Evaluation of the second spectrum, as defined in [SeidlerSolin1996]
chi2_test_gaussianity(): chi-squared test for Gaussianity of the noise timeseries, based on the second spectrum
- Noise models (nomopy.noise):
ThermalTLFModel: Model for an ensemble of thermally-activated two-level fluctuators
G.T. Seidler and S.A. Solin, Physical Review B 53, 9753 (1996)
nomopy.fhmm.FHMM#
Implementation of a factorial hidden Markov model, including (1) several expectation-maximization (EM) algorithms for model parameter fitting, (2) confidence interval generation, (3) hidden state trajectory reconstruction, and (4) data generation
nomopy.fhmm.FHMMCV#
Machinery for cross-validation and model selection through train-test splitting of noise timeseries