In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the entropy of age distribution is increasing in time. The procedure of the proposed method involves three stages, namely: 1) Prediction of the age distribution of a country’s population based on an “age-structured population model”; 2) Estimation the age distribution of each individual household size with an entropy-based formulation based on an “individual household size model”; and 3) Estimation the number of each household size based on a “total household size model”. The last stage i...
This open access book presents new developments in the field of demographic forecasting, covering bo...
The scientific methodological and functional principles of the intelligent decision support system f...
In this article, we develop a fully integrated and dynamic Bayesian approach to forecast populations...
In this paper, an entropy-based method is proposed to forecast the demographical changes of countrie...
Demographic data are fairly accessible data sets that can be used for analysis with the use of moder...
Dissertation thesis creates a complex and modern scheme for stochastic modeling of demographic proce...
The article develops a stochastic model for population forecasting. The model for forecasting the ma...
Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of popul...
This paper is concerned with the connection between two classes of population variables: measures of...
© 2016 Taylor & Francis Group, London.In the current period, the demographic development of the Repu...
We propose a new method of randomized forecasting (RF-method), which operates with models described ...
We present a theoretical model that enables to predict population distribution according to fertilit...
This paper considers the demographic process of Kazakhstan over the past 10 years, taking into accou...
Given a population at a specific time point, it is often of interest to identify the entry age into ...
An original mathematical model, previously tested by the authors on other non-demographic objects, i...
This open access book presents new developments in the field of demographic forecasting, covering bo...
The scientific methodological and functional principles of the intelligent decision support system f...
In this article, we develop a fully integrated and dynamic Bayesian approach to forecast populations...
In this paper, an entropy-based method is proposed to forecast the demographical changes of countrie...
Demographic data are fairly accessible data sets that can be used for analysis with the use of moder...
Dissertation thesis creates a complex and modern scheme for stochastic modeling of demographic proce...
The article develops a stochastic model for population forecasting. The model for forecasting the ma...
Demographic Forecasting introduces new statistical tools that can greatly improve forecasts of popul...
This paper is concerned with the connection between two classes of population variables: measures of...
© 2016 Taylor & Francis Group, London.In the current period, the demographic development of the Repu...
We propose a new method of randomized forecasting (RF-method), which operates with models described ...
We present a theoretical model that enables to predict population distribution according to fertilit...
This paper considers the demographic process of Kazakhstan over the past 10 years, taking into accou...
Given a population at a specific time point, it is often of interest to identify the entry age into ...
An original mathematical model, previously tested by the authors on other non-demographic objects, i...
This open access book presents new developments in the field of demographic forecasting, covering bo...
The scientific methodological and functional principles of the intelligent decision support system f...
In this article, we develop a fully integrated and dynamic Bayesian approach to forecast populations...