create_transition_kernels(data, transition_kernel, prior)

Creates a dictionary with observation times as keys and transition kernels as values. This assumes that the transition kernel only depends on the difference between observation times. Values are functions which take a state as argument and return a random state obtained through the transition kernel.

Arguments

• data::Dict{Real, Any}: keys are observation times, values are observed data.
• transition_kernel::Function: a function that takes time difference as argument and returns a transition kernel (a function which takes a state as argument and return a random state obtained through the transition kernel).
• prior::Distribution: a prior distribution that can be dispatched to rand().

Examples

julia> bar([1, 2], [1, 2])
1

Normalises a vector