evofr.models.renewal_model.basis_functions package
Submodules
evofr.models.renewal_model.basis_functions.basis_fns module
evofr.models.renewal_model.basis_functions.hilbert_space_gaussian_process module
- class HSGaussianProcess
Bases:
BasisFunctionImplementation of basis approximation to Gaussian processes.
- static lam(L, m)
- Parameters:
L (float)
m (int)
- static phi(L, m, x)
- Parameters:
L (float)
m (int)
x (float)
- static phi_matrix(L, m, x)
- Parameters:
L (float)
m (int)
x (float)
- class Matern(alpha=None, rho=None, nu=None, L=None, m=None)
Bases:
HSGaussianProcess- Parameters:
alpha (float | None)
rho (float | None)
nu (float | None)
L (float | None)
m (int | None)
- make_features(data)
- Parameters:
data (dict)
- Return type:
Array
- static spd(alpha, rho, nu, w)
- Parameters:
alpha (float)
rho (float)
nu (float)
w (float)
- class SquaredExponential(alpha=None, rho=None, L=None, m=None)
Bases:
HSGaussianProcess- Parameters:
alpha (float | None)
rho (float | None)
L (float | None)
m (int | None)
- make_features(data)
- Parameters:
data (dict)
- Return type:
Array
- static spd(alpha, rho, w)
- Parameters:
alpha (float)
rho (float)
w (float)
evofr.models.renewal_model.basis_functions.splines module
- class Spline(s=None, order=None, k=None)
Bases:
BasisFunction- Parameters:
s (Array | None)
order (int | None)
k (int | None)
- make_features(data=None, T=None)
- Parameters:
data (dict | None)
T (float | None)
- Return type:
Array
- static matrix(t, s, order)
Construct matrix for spline of order ‘order’ with knots ‘s’ at points ‘t’.
- class SplineDeriv(s=None, order=None, k=None)
Bases:
object- Parameters:
s (Array | None)
order (int | None)
k (int | None)
- make_features(data=None, T=None)
- Parameters:
data (dict | None)
T (float | None)
- Return type:
Array
- static matrix(t, s, order)
Construct matrix for spline derivative of order ‘order’ with knots ‘s’ at points ‘t’.