bio_expression.MH Class Reference

Class performing draws from densities for Bayesian estimation using Metropolis-Hastings algorithm. More...

Inheritance diagram for bio_expression.MH:

Public Member Functions
def	__init__ (self, beta, density, warmup, steps)
Public Member Functions inherited from bio_expression.Expression
def	__init__ (self)
	Constructor.
def	getExpression (self)
def	getID (self)
def	__str__ (self)
def	__neg__ (self)
def	__add__ (self, expression)
def	__radd__ (self, expression)
def	__sub__ (self, expression)
def	__rsub__ (self, expression)
def	__mul__ (self, expression)
def	__rmul__ (self, expression)
def	__div__ (self, expression)
def	__rdiv__ (self, expression)
def	__truediv__ (self, expression)
	Support for Python version 3.x. More...
def	__rtruediv__ (self, expression)
	Support for Python version 3.x. More...
def	__mod__ (self, expression)
def	__pow__ (self, expression)
def	__rpow__ (self, expression)
def	__and__ (self, expression)
def	__or__ (self, expression)
def	__eq__ (self, expression)
def	__ne__ (self, expression)
def	__le__ (self, expression)
def	__ge__ (self, expression)
def	__lt__ (self, expression)
def	__gt__ (self, expression)

Public Attributes
	type
	beta
	density
	warmup
	steps
	operatorIndex
Public Attributes inherited from bio_expression.Expression
	operatorIndex

Detailed Description

Class performing draws from densities for Bayesian estimation using Metropolis-Hastings algorithm.

Values of Beta parameters are drawn from a given density function using a Metropolis-Hastings algorithm. Example:

BETA = {ASC_CAR, ASC_TRAIN, B_TIME, B_COST}
prob = bioLogit(V,av,CHOICE)
rowIterator('obsIter') 
likelihood = Prod(prob,'obsIter')
BIOGEME_OBJECT.BAYESIAN = MH(BETA,likelihood)

Definition at line 1139 of file bio_expression.py.

Constructor & Destructor Documentation

def bio_expression.MH.__init__	(		self,
			beta,
			density,
			warmup,
			steps
	)

Parameters

beta	a list of the form {beta1, beta2,...} where beta1, beta2, etc. are defined by the Beta expression.
density	valid expression representing the density to draw from.
warmup	number of steps of the Markov chain to perform to reach stationarity.
steps	number of steps to skip between two draws.

Definition at line 1150 of file bio_expression.py.

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The documentation for this class was generated from the following file:

• bio_expression.py