This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided t...This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided the theoretical basis for this study. A survey research design involving a stratified sampling technique was adopted. The descriptives on transport modes, amount and time spent revealed that 10 (76.9%) males and 3 (23.1%) females preferred bicycle as means of transportation, 7 (58.3%) males and 5 (41.7%) females preferred motorcycle, while a significant proportion 90 (53.9%) males and 77 (46.1%) females preferred tricycle, 80 (63.0%) males and 47 (37.0%) females preferred cars/taxis, and 12 (46.2%) males and 14 (53.8%) females preferred mass transit bus. However, 14 (46.7%) males and 16 (53.3%) females in marshy terrain and coastal locations preferred canoes and boats. The result of the logistic regression model revealed that gender modal preference is more likely to be influenced by mode of transportation with a beta weight of 1.140, safety considerations 1.139, ownership of transport 1.135 and distance to place of work 1.073. Hence, this study recommends that a combination of these factors should be incorporated into transport planning to achieve effective transport planning and sustainable development in the Yenagoa metropolis.展开更多
基于马尔可夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)方法的α稳定分布参数估计具有良好的性能,但不合适的提议函数常导致算法不收敛或混合性能不好。针对提议函数难以选择的问题,提出了一种基于自适应Metropolis算法的非对称α稳...基于马尔可夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)方法的α稳定分布参数估计具有良好的性能,但不合适的提议函数常导致算法不收敛或混合性能不好。针对提议函数难以选择的问题,提出了一种基于自适应Metropolis算法的非对称α稳定分布参数估计新方法。该方法利用Markov链的历史信息自动调整提议函数的协方差矩阵,使其不断地逼近目标分布,从而获得更好的估计结果。理论分析和仿真结果表明,此方法不仅能准确地估计出α稳定分布的4个参数,而且具有良好的鲁棒性和灵活性。展开更多
文摘This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided the theoretical basis for this study. A survey research design involving a stratified sampling technique was adopted. The descriptives on transport modes, amount and time spent revealed that 10 (76.9%) males and 3 (23.1%) females preferred bicycle as means of transportation, 7 (58.3%) males and 5 (41.7%) females preferred motorcycle, while a significant proportion 90 (53.9%) males and 77 (46.1%) females preferred tricycle, 80 (63.0%) males and 47 (37.0%) females preferred cars/taxis, and 12 (46.2%) males and 14 (53.8%) females preferred mass transit bus. However, 14 (46.7%) males and 16 (53.3%) females in marshy terrain and coastal locations preferred canoes and boats. The result of the logistic regression model revealed that gender modal preference is more likely to be influenced by mode of transportation with a beta weight of 1.140, safety considerations 1.139, ownership of transport 1.135 and distance to place of work 1.073. Hence, this study recommends that a combination of these factors should be incorporated into transport planning to achieve effective transport planning and sustainable development in the Yenagoa metropolis.
文摘基于马尔可夫链蒙特卡罗(Markov chain Monte Carlo,MCMC)方法的α稳定分布参数估计具有良好的性能,但不合适的提议函数常导致算法不收敛或混合性能不好。针对提议函数难以选择的问题,提出了一种基于自适应Metropolis算法的非对称α稳定分布参数估计新方法。该方法利用Markov链的历史信息自动调整提议函数的协方差矩阵,使其不断地逼近目标分布,从而获得更好的估计结果。理论分析和仿真结果表明,此方法不仅能准确地估计出α稳定分布的4个参数,而且具有良好的鲁棒性和灵活性。
