软计算与硬计算融合的中国石油需求预测

近年来,随着我国经济的高速增长,石油作为重要的战略资源,在经济发展中发挥着越来越重要的作用。运用软计算和硬计算相融合的方法对我国2004—2015年的石油需求进行了预测。首先介绍了软计算和硬计算融合的串联模式,然后构建了影响我国石油需求(石油消费量)的主要指标,即国内生产总值(GDP)、人口总量、能源消耗量和居民消费水平。通过分析这些指标的数据特征,得出它们随时间的推移呈现增长的趋势。根据这一结论,运用软计算和硬计算融合中的串联模式,用硬计算中的龚珀资(Gompertz)增长曲线预测法来预测影响石油需求的4个指标以及石油需求量2004—2015年的值。在这些数据的基础上,再用软计算中的BP人工神经网络,对我国2004-2015年的石油需求量进行了预测。最后通过对HC和SC预测的石油需求量进行加权平均,得到了最终的预测结果。     

A new extended generalized Gompertz distribution with statistical properties and simulations

Abstract

Statistical distributions are very useful in describing and predicting real world phenomena. In many applied areas there is a clear need for the extended forms of the well-known distributions. Generally, the new distributions are more flexible to model real data that present a high degree of skewness and kurtosis. The choice of the best-suited statistical distribution for modeling data is very important.

In this article, we proposed an extended generalized Gompertz (EGGo) family of EGGo. Certain statistical properties of EGGo family including distribution shapes, hazard function, skewness, limit behavior, moments and order statistics are discussed. The flexibility of this family is assessed by its application to real data sets and comparison with other competing distributions. The maximum likelihood equations for estimating the parameters based on real data are given. The performances of the estimators such as maximum likelihood estimators, least squares estimators, weighted least squares estimators, Cramer-von-Mises estimators, Anderson-Darling estimators and right tailed Anderson-Darling estimators are discussed. The likelihood ratio test is derived to illustrate that the EGGo distribution is better than other nested models in fitting data set or not. We use R software for simulation in order to perform applications and test the validity of this model.     

On the likelihood estimation of the parameters of Gompertz distribution based on complete and progressively Type-II censored samples

In this paper, by considering a progressively Type-II censored sample from the two-parameter Gompertz distribution, a necessary and sufficient condition is established for the existence and uniqueness of the maximum-likelihood estimates of the shape and scale parameters. The results for the special cases of complete and ordinary Type-II right censored samples are then deduced. Several numerical examples from the literature are presented for the purpose of illustrating the established results.     

The Hazard-Product method of generalization: Application to the gompertz and exponentiated Half-Normal distributions

As new data sources arrive, novel methods of defining undiscovered distributions are increasingly useful. In this presentation, the Hazard-Product method of generalizing survival functions is introduced. Some limitations and considerations are discussed, and a new extensions of the Gompertz and Half-Normal models are proposed. Finally, basic moment and estimation properties of the models are given, and two real data sets are analyzed.     

基于能源消费的长三角地区碳排放趋势研究

采用IPCC碳排放技术指南提供的能源消费碳排放计算公式对长三角地区1996年—2010年能源消费的碳排放量进行计算,在此基础上分别建立灰色预测GM（1,1）模型和Gompertz曲线模型预测和分析长三角地区未来碳排放趋势。长三角地区能源消费碳排放量正处于而且还将处于持续增长阶段,短期内难以达到峰值;长三角地区应积极发展新能源,逐步降低煤炭在能源消费中的比重,进一步优化能源消费结构,控制和降低能源消费碳排放量。     

The Strehler–Mildvan correlation from the perspective of a two-process vitality model

The Strehler and Mildvan (SM) general theory of ageing and mortality provides a mechanism-based explanation of Gompertz's law and predicts a log-linear relationship between the two Gompertz coefficients, known as the SM correlation. While the SM correlation is supported by data from developed countries before the second half of the twentieth century, the recent breakdown of the correlation pattern in these countries has prompted demographers to conclude that SM theory needs to be reassessed. In this paper we use a newly developed two-process vitality model to explain the SM correlation and its breakdown in terms of asynchronous trends in acute (extrinsic) and chronic (intrinsic) mortality factors. We propose that the mortality change in the first half of the twentieth century is largely determined by the elimination of immediate hazards to death, whereas the mortality change in the second half is primarily driven by the slowdown of the deterioration rate of intrinsic survival capacity.     

Modelling Deceleration in Senescent Mortality

Mortality deceleration is the observed but yet to be understood phenomenon that the increase in the late-life death rate slows down after a certain species-related advanced age. Various definitions of onsets of mortality deceleration are examined. A new distribution based on the Strehler-Mildvan theory of aging takes on the required shapes. The application is done on mortality data from the 1892 cohort of Swedish women and on Mediterranean fruit flies.     

Gompertz model with time-dependent covariate in the presence of interval-, right- and left-censored data

In this paper, the Gompertz model is extended to incorporate time-dependent covariates in the presence of interval-, right-, left-censored and uncensored data. Then, its performance at different sample sizes, study periods and attendance probabilities are studied. Following that, the model is compared to a fixed covariate model. Finally, two confidence interval estimation methods, Wald and likelihood ratio (LR), are explored and conclusions are drawn based on the results of the coverage probability study. The results indicate that bias, standard error and root mean square error values of the parameter estimates decrease with the increase in study period, attendance probability and sample size. Also, LR was found to work slightly better than the Wald for parameters of the model.     

Estimation of the parameters of the Gompertz distribution under the first failure-censored sampling plan

This article presents the goodness-of-fit tests for the Laplace distribution based on its maximum entropy characterization result. The critical values of the test statistics estimated by Monte Carlo simulations are tabulated for various window and sample sizes. The test statistics use an entropy estimator depending on the window size; so, the choice of the optimal window size is an important problem. The window sizes for yielding the maximum power of the tests are given for selected sample sizes. Power studies are performed to compare the proposed tests with goodness-of-fit tests based on the empirical distribution function. Simulation results report that entropy-based tests have consistently higher power than EDF tests against almost all alternatives considered.     

Gompertz-power series distributions

ABSTRACT

In this article, we introduce the Gompertz power series (GPS) class of distributions which is obtained by compounding Gompertz and power series distributions. This distribution contains several lifetime models such as Gompertz-geometric (GG), Gompertz-Poisson (GP), Gompertz-binomial (GB), and Gompertz-logarithmic (GL) distributions as special cases. Sub-models of the GPS distribution are studied in details. The hazard rate function of the GPS distribution can be increasing, decreasing, and bathtub-shaped. We obtain several properties of the GPS distribution such as its probability density function, and failure rate function, Shannon entropy, mean residual life function, quantiles, and moments. The maximum likelihood estimation procedure via a EM-algorithm is presented, and simulation studies are performed for evaluation of this estimation for complete data, and the MLE of parameters for censored data. At the end, a real example is given.