biomass consumption in one state will interact with that in other states through unknown media. Similar with direct spatial dependence, the indirect spatial dependences are positive as well,
apart from those in 2001, 2002 and 2005, and the obvious division before/after 2009 in indirect spatial dependence is observed as well. The argument for the implications of these in the case of direct spatial dependence can be also applied here as well. Compared to the R2 of model with direct spatial dependence (0.3843), the R2 of model with indirect spatial dependence (0.3704) is slightly smaller, potentially indicating that the spatial dependence among biomass consumption is direct rather than indirect. In other words, biomass consumption of one state tends to be impacted directly by its neighboring states'. However, the R2 for these two models are relatively low, indicating a somewhat limited explanatory power of models, and therefore it needs cautions when applying these models for sustainable biomass policy-making.
The preceding analysis for direct and indirect spatial dependence can be also applied to both the period of 2009e2012 and the period of 2005e2008 (Tables 4e6). However, the levels of spatial
dependence, regardless of direct or indirect, are increasing over
biomass consumption in one state will interact with that in other states through unknown media. Similar with direct spatial dependence, the indirect spatial dependences are positive as well,apart from those in 2001, 2002 and 2005, and the obvious division before/after 2009 in indirect spatial dependence is observed as well. The argument for the implications of these in the case of direct spatial dependence can be also applied here as well. Compared to the R2 of model with direct spatial dependence (0.3843), the R2 of model with indirect spatial dependence (0.3704) is slightly smaller, potentially indicating that the spatial dependence among biomass consumption is direct rather than indirect. In other words, biomass consumption of one state tends to be impacted directly by its neighboring states'. However, the R2 for these two models are relatively low, indicating a somewhat limited explanatory power of models, and therefore it needs cautions when applying these models for sustainable biomass policy-making.The preceding analysis for direct and indirect spatial dependence can be also applied to both the period of 2009e2012 and the period of 2005e2008 (Tables 4e6). However, the levels of spatialdependence, regardless of direct or indirect, are increasing over
การแปล กรุณารอสักครู่..
