This paper introduces a new stochastic diffusion process to model the electricity production from natural gas sources (as a percentage of total electricity production) in the United States. The method employs trend function analysis to generate fits and forecasts with both conditional and unconditional estimated trend functions. Parameters are estimated using the maximum likelihood (ML) method, based on discrete sampling paths of the variable "electricity production from natural gas sources in the United States" with annual data from 1990 to 2021. The results show that the proposed model effectively fits the data and provides dependable medium-term forecasts for 2022-2023.

翻译：本文提出了一种新型随机扩散过程，用于建模美国天然气发电量（占总发电量的百分比）。该方法通过趋势函数分析，利用条件与非条件估计趋势函数进行拟合与预测。参数估计采用最大似然法，基于变量“美国天然气发电量”的离散采样路径（使用1990年至2021年的年度数据）。结果表明，所提模型能有效拟合数据，并为2022-2023年提供了可靠的中期预测。