Index

_

__call__() (model.Model method)

B

bernoulli() (in module distributions)

beta() (in module distributions) binomial() (in module distributions)

C

cauchy() (in module distributions)

D

direction_slice() (sampyl.Slice method)

discrete_uniform() (in module distributions) distributions (module)

E

exponential() (in module distributions)

F

fails_constraints() (in module distributions) freeze() (state.State method)

fromfunc() (state.State static method) fromvector() (state.State method)

H

half_cauchy() (in module distributions)

Hamiltonian (class in sampyl)

L

laplace() (in module distributions)

M

Metropolis (class in sampyl) Model (class in model)

model (module) (sampyl.Sampler attribute)

N

normal() (in module distributions)

NUTS (class in sampyl)

P

poisson() (in module distributions)

S

sample() (sampyl.Hamiltonian method) (sampyl.Metropolis method) (sampyl.NUTS method) (sampyl.Sampler method) (sampyl.Slice method) Sampler (class in sampyl) sampler (sampyl.Sampler attribute) sampyl (module), [1], [2], [3], [4], [5] Slice (class in sampyl)

State (class in state) state (module) (sampyl.Sampler attribute) step() (sampyl.Hamiltonian method) (sampyl.Metropolis method) (sampyl.NUTS method) (sampyl.Sampler method) (sampyl.Slice method) student_t() (in module distributions)

T

tovector() (state.State method)

U

uniform() (in module distributions)

W

weibull() (in module distributions)