examples
A model to use for the examples in this class
Define a model to use throughout the examples in this file
Breeze MCMC, random walk Metropolis Hastings with different values of delta
Breeze MCMC, single site Metropolis Hastings With different values of delta
Remove duplicate readings where the temperature is exactly the same
Filter observations as a batch, return the state and credible intervals
An example showing real time filtering of observations arriving as a stream
Filter the simulated seasonal poisson data in a batch
To determine the mll variance at a given set of parameters, we must perform iterations of the PMMH algorithm with the proposal distribution being the identity This allows us to determine the optimal number of particles used in the PMMH, at a set of "good" parameters, typically it is said the mll variance should be one
Test Multiple methods with the same data
Simulate a brownian motion state space
Simulate an Ornstein-Uhlenbeck state space
Simulate 100 observaitions from a simple bernoulli model
Simulate a poisson model, with seasonal rate parameter
Graph DSL version, random walk metropolis algorithm
Using akka-streaming, random walk metropolis algorithm with different values of delta