opendose_poppk.MAPEstimator

class opendose_poppk.MAPEstimator(pk: PKModel | None = None, covariate_model: CovariateModel | None = None, sigma_obs: float = 1.0)

Bayesian individual parameter estimation (Maximum A Posteriori).

Finds individual etas that minimize:

obj = Σ[(C_obs − C_pred)² / σ²] + Σ[ηᵢ² / ωᵢ²]

└─ data fidelity ──────┘ └─ population prior ─┘

Example

>>> est = MAPEstimator(pk, covariate_model=cov)
>>> res = est.fit(
...     times=np.array([1, 2, 4, 6]),
...     obs  =np.array([6.8, 7.5, 5.9, 4.1]),
...     patient_covariates={"weight": 90, "crcl": 50},
...     dose=1000.0
... )
>>> print(res["params_map"])

__init__(pk: PKModel | None = None, covariate_model: CovariateModel | None = None, sigma_obs: float = 1.0)

Methods

__init__([pk, covariate_model, sigma_obs])
fit(times, obs, patient_covariates, dose[, ...])	Fit individual parameters for a patient.