Box-Jenkins modelsIntervention analysis is a relatively new branch of time series analysis. The power of this technique, which gives the probability that changes in mean level can be distinguished from natural data variability, is quite sensitive to the way the data are collected. The principal ...
73. Jenkins, G. M. & Watts, D. G. Spectral analysis and its applications. (Holden-Day, 1968). 74. Schwarz, A. J. & McGonigle, J. Negative edges and soft thresholding in complex network analysis of resting state functional connectivity data. NeuroImage 55, 1132–1146, doi: 10.1016/...
DEA can be used when the relationship between variables does not have a known mathematical function [121]. DEA is a flexible method that can be adapted to the data [122]. Moreover, multiple input and output variables in different units can be analyzed at the same time, without a priori ...
variables from 14 different sources were applied. Of those 24 variables, 8 are national-level indexes and 16 are rasters and polygons data sets that were overlayed to the 6888 point data set on ArcGIS. The theoretical framework and data selection are summarised below, and visualised in ...
Building ARIMA seasonal model and cross-correlation of the malaria series with the series of meteorological variables Box-Jenkins approach [42] was used to model independently each time series. The best seasonal autoregressive integrated moving average (SARIMA) model was selected with the lowest Akaike...
Table 4 Results from LASSO Exposures selected in the final model Full size table Regarding the exposures during childhood, a total of 23 variables was selected by LASSO and 16 of them were kept in the final multivariable model (p-value ≤ 10%) (Fig. 3 and Table 4). High intakes of...
Suitability of the species growth was most probable for year 2015 for the variables of air temperature and land surface temperature. A spatial analysis was complementarily presented to visualize the correlation of variables for the best suitability of the species growth. This study pres...
1). The inputs (exogenous variables and parameters) of the model are: service demand curves, supply curves (e.g. primary energy resources such as wind power or availability of imports), and techno-economic parameters for each technology/process (e.g. technology efficiencies and availability ...
this includes extra populations to expand information in Africa and Oceania. They gathered environmental data for nine continuous climate variables that have a strong impact on human physiology; however, these climate variables are simple proxies for selective pressures that are likely to be much more...
Only three variables, corresponding to the areas of peaks 2, 5 and 8, were used to generate the discriminant functions. In order to place an unknown sample, the values of the three variables are inserted into the equations, and the unknown sample was grouped according to the discriminant ...