The age-drift model consisted of the 18 indicators for age, and the four time periods entered as a continuous variable, to model trends not attributable to either period or cohort.
Another commonly used strategy is to apply a log-additive genetic model (trend test) to the genotype distributions for ranking association with disease [7].
It will often not be obvious which function to choose to model trends in the data, so an approach using basis functions and expanding these to different orders will be of advantage, as in equation (4).
In contrast to most other methods commonly used to model trends in time series data, a key strength of the FDA approach is that it makes no parametric assumptions about age or time effects.
On longer time scales, a very important task will be to try to jointly model trends in the mesosphere and thermosphere with trends in the stratosphere, i.e., developing one holistic unified framework.
The methods to model trends in space and time, handle correlation structures in the data, estimate effects, test hypotheses, and predict future outcomes are relatively new and without extensive application in environmental public health.
In the along-wind direction, the aerodynamic damping ratios of the 180° helical model exhibit similar trends to those of the square model.
By the comparative analysis of the models' data outputs, the best performed models having similar trends to the observed data predicted the future summer monsoon as a decline of 89.45 mm by model beccr to 60.07 mm by model cccma.
The AGE pilot was conducted to assess the feasibility of generalizing the Distribute model from ILI trends to monitoring other syndromes.
The best performed models having similar trends to the historical observed temperature data analysis predicted that the future summer mean temperature has been predicted to increase by 0.59 °C (model bccr) and 0.743 °C (model cccma) from 2015 to 2054.
