The paper outlines the software infrastructure, indicators and model and data components.
We also show how our results extend to empirically interesting dynamic versions of the model with both lagged observed outcomes, lagged indicators, and models with factor loads.
This proposed IDA can be useful for error form indicators and models by providing a substitute method to facilitate enhanced evaluation of watershed models within an uncertainty framework.
A novel intelligent reference method for iris segmentation-level fusion is presented, which uses a learning-based approach predicting ground truth segmentation performance from quality indicators and model-based fusion to create combined boundaries.
The design of such policies is currently hampered by the limited understanding of socioeconomic drivers of and pressures on biodiversity as well as by lacking data, indicators and models.
Three logistic regression models were constructed; Model A included non-clinical risk indicators, Model B included clinical risk indicators and Model C included both non-clinical and clinical risk indicators.
Allocation models can employ individual-level data on resource use and need indicators, but because of data limitations (especially the lack of survey data with adequate sample size by region), they are often based on need indicators and models for small areas (e.g., premature mortality rates or rates of morbidity)[ 5, 7].
A much needed first step is, therefore, building a clear conceptual framework that defines and differentiates IHPs and starts to build indicators and models linking the values underpinning partnership working to their benefits and effectiveness in institutional strengthening and capacity building along with identifying their niche within the development cooperation field.
Because of the complexity, sheer number of variables, and limitations of empirical data on land changes, models are often used to illustrate and estimate values for landscape indicators, and those models have several problems.
