smfsb

Type Members

trait CsvRow[T] extends AnyRef

Type class for vectors that can be rendered to a CSV string (and a Breeze DenseVector[Double]), extended by State
implicit class CsvRowSyntax[T] extends AnyRef

Syntax for CsvRow
trait DataSet[D] extends AnyRef

Data set type class, for ABC methods
type DoubleState = DenseVector[Double]

Alias for a Breeze DenseVector[Double]
type HazardVec = DenseVector[Double]

Type for a SPN hazard vector
type IntState = DenseVector[Int]

Alias for a Breeze DenseVector[Int]
type LogLik = Double

Type representing log-likelihoods - just an alias for Double.
Type representing log-likelihoods - just an alias for Double. All likelihoods in this library are on a log scale. There should be no raw likelihoods passed into or out of any user-facing function.
case class MarkedSpn[S](species: List[String], m: S, pre: DenseMatrix[Int], post: DenseMatrix[Int], h: (S, Time) ⇒ HazardVec)(implicit evidence$2: State[S]) extends Spn[S] with Product with Serializable

Case class for SPNs that include an initial marking
sealed trait Spn[S] extends AnyRef

Main trait for stochastic Petri nets (SPNs)
trait State[S] extends CsvRow[S]

State type class, with implementations for Breeze DenseVector Ints and Doubles
trait Thinnable[F[_]] extends AnyRef

A type class for things which can be "thinned", with an implementation for Stream.
A type class for things which can be "thinned", with an implementation for Stream. Useful for MCMC algorithms.
implicit class ThinnableSyntax[T, F[T]] extends AnyRef

Provision of the .thin syntax for Thinnable things
type Time = Double

Type representing time, but just an alias for Double
type Ts[S] = List[(Time, S)]

The main time series class, for representing output from simulation functions, and for observed time course data
case class UnmarkedSpn[S](species: List[String], pre: DenseMatrix[Int], post: DenseMatrix[Int], h: (S, Time) ⇒ HazardVec)(implicit evidence$1: State[S]) extends Spn[S] with Product with Serializable

Case class for SPNs without an initial marking

Value Members

object Abc

Functions for parameter inference using ABC (and ABC-SMC) methods
object Mcmc

Functions for constucting generic Metropolis-Hastings MCMC algorithms, and associated utilities.
Functions for constucting generic Metropolis-Hastings MCMC algorithms, and associated utilities. Can be used in conjunction with an unbiased estimate of marginal model likelihood for constructing pseudo-marginal MCMC algorithms, such as PMMH pMCMC.
object Mll

Functions associated with particle filtering of Markov process models against time series data and the computation of marginal model likelihoods.
object Sim

Functions for simulating data associated with a Markov process given an appropriate transition kernel.
object SpnModels

Some example SPN models, each of which can be instantiated with either discrete or continous states.
object Step

Functions which accept a Spn and return a function for simulating from the transition kernel of that model
implicit val dvdState: State[DoubleState]

Evidence that DoubleState belongs to the State type class
implicit val dviState: State[IntState]

Evidence that IntState belongs to the State type class
implicit val streamThinnable: Thinnable[Stream]

A Thinnable instance for Stream
implicit val tsdsDs: DataSet[Ts[DoubleState]]

Evidence that Ts[DoubleState] is a DataSet
implicit val tsisDs: DataSet[Ts[IntState]]

Evidence that Ts[IntState] is a DataSet

package smfsb

Type Members

trait CsvRow[T] extends AnyRef

implicit class CsvRowSyntax[T] extends AnyRef

trait DataSet[D] extends AnyRef

type DoubleState = DenseVector[Double]

type HazardVec = DenseVector[Double]

type IntState = DenseVector[Int]

type LogLik = Double

case class MarkedSpn[S](species: List[String], m: S, pre: DenseMatrix[Int], post: DenseMatrix[Int], h: (S, Time) ⇒ HazardVec)(implicit evidence$2: State[S]) extends Spn[S] with Product with Serializable

sealed trait Spn[S] extends AnyRef

trait State[S] extends CsvRow[S]

trait Thinnable[F[_]] extends AnyRef

implicit class ThinnableSyntax[T, F[T]] extends AnyRef

type Time = Double

type Ts[S] = List[(Time, S)]

case class UnmarkedSpn[S](species: List[String], pre: DenseMatrix[Int], post: DenseMatrix[Int], h: (S, Time) ⇒ HazardVec)(implicit evidence$1: State[S]) extends Spn[S] with Product with Serializable

Value Members

object Abc

object Mcmc

object Mll

object Sim

object SpnModels

object Step

implicit val dvdState: State[DoubleState]

implicit val dviState: State[IntState]

implicit val streamThinnable: Thinnable[Stream]

implicit val tsdsDs: DataSet[Ts[DoubleState]]

implicit val tsisDs: DataSet[Ts[IntState]]

Inherited from AnyRef

Inherited from Any

Ungrouped