Cox Processes Associated with Spatial Copula Observed through Stratified Sampling

Copula Processes

We define a copula process which describes the dependencies between arbitrarily many random variables independently of their marginal distributions. As an example, we develop a stochastic volatility model, Gaussian Copula Process Volatility (GCPV), to predict the latent standard deviations of a sequence of random variables. To make predictions we use Bayesian inference, with the Laplace approxi...

statistical road classification applied to stratified spatial sampling of road traffic noise in urban areas

monitoring of road traffic noise is becoming an important issue in modern cities due to the spreading of noise pollution and the extension of monitored areas. thus, the stratified spatial sampling is frequently applied to reduce the costs and provide adequate accuracy in order to obtain reliable noise maps. the definition of the strata in the sampling may refer to the legislative classification...

Copula Estimation of Distribution Algorithm Sampling from Clayton Copula

Estimation of Distribution Algorithms (EDAs) are implemented mainly by the three steps: selecting the promising subset from the current population, modeling the distribution of the selected population and sampling from the estimated model. Modeling and sampling are key steps of EDAs. They are also research topic of copula theory to represent the multivariate joint distribution by a copula and t...

Moment estimation methods for stationary spatial Cox processes - a comparison

In the present paper we consider the problem of fitting parametric spatial Cox point process models. We concentrate on the moment estimation methods based on the second order characteristics of the point process in question. These methods represent a simulation-free faster-to-compute alternative to the computationally intense maximum likelihood estimation. We give an overview of the available m...

Stratified Sampling Method