Multiple Variables Cdf Estimator

A Multiple Variables Cdf Estimator estimates a conditional distribution function of variable Z₁ at a location u given some neighboring information. This information can consist of outcomes of several different variables Z₂,..., Z_Nv. A Multiple Variables Cdf Estimator can estimate parametric cdf's (usually Gaussian) or non-parametric cdf's, using different approaches: kriging, search trees (SNESIM).

Refinement of

Assignable

Notations

A		a type that is a model of cdf estimator
a		an object of type A
f		an object of a type that models CDF
u		an object of a type that models a Location
first,last		two models of Input Iterator (see STL) iterating on a range of models of Neighborhood

Valid Expressions

• Estimate cdf

  a(u,first,last,f)

  Return type:		int
  Semantics:		estimates the ``parameters'' of cdf f (mean and variance in the case of a Gaussian cdf, or the probabilities Prob(Z$\le$zi) = F(zi), i = 1,..., n, if F is non-parametric). The returned value is 0 if no problem was encountered during the execution of the function. If the returned value is different from 0 (i.e. the estimation of f failed), ccdf f has not been modified by the function call

Models

• gaussian_cdf_coKestimator: estimator of a gaussian cdf using cokriging (coK)