Maximum Entropy Methods for Loss Data Analysis: Aggregation and Disaggregation Problems

Spatial Disaggregation of Agricultural Production Data by Maximum Entropy

In this paper we develop a dynamic data-consistent way for estimating agricultural land use choices at a disaggregate level (district-level), using more aggregate data (regional-level). The disaggregation procedure requires two steps. The first step consists in specifying and estimating a dynamic model of land use at the regionallevel. In the second step, we disaggregate outcomes of the aggrega...

Maximum Entropy Data Analysis

Iterative aggregation: disaggregation methods and ordering algorithms

The paper presents some modifications of two-level methods for computing stationary probability distribution vector of large discrete time Markov chains. The approach considered is an iterative aggregation disaggregation method. Two types of permuting the events are considered in order to improve the convergence.

The Effect of Observation Data Sampling Methods on Infiltration Areas by Maximum Entropy Model

Statistical modeling methods are based on multivariate regression methods and require the presence and absence location of data for the construction of the model. In most cases, there is no trustworthy absence data. Therefore, other methods that are based only on the presence of the phenomenon are used. Considering the importance of modeling - saving time and cost and the probable prediction of...

Ela Error Propagation Formula of Multi-level Iterative Aggregation-disaggregation Methods for Non-symmetric Problems

Iterative aggregation-disaggregation methods for numerical computing of stationary probability distribution vectors of stochastic matrices are studied. The methods can use arbitrary numbers of levels and of smoothing steps. A formula for the error propagation is derived. Using this formula, some asymptotic convergence properties of these methods for non-symmetric problems are demonstrated.