Multivariate history#79
Conversation
- Change the models to hold vectors of parameters instead of single
parameters
- Update methods to return multivariate histories
- Update tests
Steps
- Update general interface for `AbstractPointProcess`
- Update `simulation.jl`
- Update homogeneous Poisson and related methods
- Update inhomogeneous Poisson and related methods
- Update hypothesis tests
- They work only for univariate processes. Generalization for the
futrue
- Ignore Hawkes processes, since they will be implemented in another PR
- Takes an array of parameters - Methods like `ground_intensity` return an array - Added methods with an argument `d::Int` to get the values from specific dimensions
This reverts commit 90f08d6. Instead of making all processes multivariate, implement tem separately. - `AbstractMultivariateProcess` - `IndependenteMultivariateProcess` - `DependentMultivariateProcess`? - Other processes, such as `MultivariateHawkesProcess`
Univariate and multivariate processes are different types. Implementation for univariate processes remained unchanged.
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PointProcesses.jl/test/inhomogeneous_poisson_process.jl
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PointProcesses.jl/test/multivariate_poisson_process.jl
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Implementation of multivariate processes. Discussion in Issue #73
HistoryContains an array
timeswith the event times, an arraymarkswith corresponding marks, and another arraydimswith corresponding dimensionUnivariatePointProcessandMultivariatePointProcessAll previous implementations remained unchanged, but now these processes are subtypes of
UnivariatePointProcess.Multivariate processes were implemented separetely as
MultivariatePointProcess. This allowed the implementation ofIndependentMultivariateProcessandMultivariatePoissonProcesssimply using an array of univariate processes.