Merge pull request #8 from dm13450/dev

Event Probabilities

README.md

@@ -2,6 +2,10 @@
 
 [![Coverage Status](https://coveralls.io/repos/github/dm13450/HawkesProcesses.jl/badge.svg?branch=master)](https://coveralls.io/github/dm13450/HawkesProcesses.jl?branch=master)
 
+[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://dm13450.github.io/HawkesProcesses.jl/stable)
+
+[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://dm13450.github.io/HawkesProcesses.jl/dev)
+
 # HawkesProcesses
 
 A Julia package for fitting, analysing and plotting Hawkes processes.

src/HawkesProcesses.jl

@@ -14,6 +14,7 @@ module HawkesProcesses
     include("time_change.jl")
     include("compensator.jl")
     include("utils.jl")
+    include("event_probability.jl")
 
     export fit, HierarchicalHawkesFit
 

src/event_probability.jl

@@ -0,0 +1,23 @@
+"""
+    event_probability(startT, endT, events, background, kappa, kernel)
+Forecast the probability of an event in defined time window. 
+
+# Arguments
+* `startT::Number`: Left boundary of the forecasting window.
+* `endT::Number`: Right boundary of the forecasting window.  
+* `events::Array{<:Number,1}`: Observed events
+* `background`: Background rate
+* `kappa::Float64`: Kappa value
+* `kernel::Distribution`: Kernel distribution
+
+# Notes
+* As we are integregating the intensity function on a constant background, constant kappa and distriubtion for the kernel are supported. 
+
+"""
+
+function event_probability(startT::Number, endT::Number, events::Array{<:Number}, background::Number, kappa::Number, kernel::Distribution)
+
+    filter!(x-> x <= endT, events)
+    background*(endT - startT) + kappa * sum( cdf.(kernel, endT .- events) .- cdf.(kernel, startT .- events) )
+
+end

test/event_probability_test.jl

@@ -0,0 +1,27 @@
+
+@testset "Event Probabilities" begin 
+
+    @testset "Basic Test" begin 
+
+        bg = 0.5
+        kappa = 0.5
+        kern = Distributions.Exponential(1/0.5)
+        events = [1,2,3]
+        startT = 4
+        endT = 5
+        prob = HawkesProcesses.event_probability(startT, endT, events, bg, kappa, kern)
+        @test isa(prob, Number)
+    end
+
+    @testset "Value Test" begin 
+        bg = 0.5
+        kappa = 0.5
+        kern = Distributions.Exponential(1/0.5)
+        events = [1,2,3]
+        startT = 400
+        endT = 500
+        prob = HawkesProcesses.event_probability(startT, endT, events, bg, kappa, kern)
+        @test prob == 50
+    end
+
+end

test/runtests.jl

@@ -13,7 +13,8 @@ my_tests = ["event_difference_test.jl",
             "compensator_test.jl",
             "time_change_test.jl",
             "likelihood_test.jl",
-            "test_utils.jl"]
+            "test_utils.jl",
+            "event_probability_test.jl"]
 
 println("Running tests: ")