This template agreement is provided courtesy of Kate Mertes. The scope of the index remains a pragmatic extension of r and is therefore used in a context where a linear operating agreement is desired. It is not designed as a tool to study new functional associations in data (for example. B the maximum information coefficient32). However, its use could go beyond the symmetrical comparison of the dataset agreement and combine the list of existing methods2 to characterize the model`s performance against a reference. The index has also been demonstrated here by timed data case studies, but it should also be used for each pair of vectors of any type of data, just like r. The index has the desirable additional property that if there is no additive or multiplier distortion, it takes the value of the correlation coefficient. In the event of distortion, the index takes a value of less than r according to a multiplication coefficient α which can only take a value between 0 and 1. The equation (10) effectively demonstrates (see Additional Information) that: the advantage of this property is that the value of the index can be immediately compared to r, which is a metric that most practitioners know. Any deviation from r indicates an increase in the differences in proportion to α. Some of the most popular index futures are stock-based. However, each product can use a different multiple to determine the price of the futures contract.
For example, the futures contract is valued at 250 times the S-P 500 contract, i.e. if the index trades at 3,400 points, the market value of the contract would be 3,400 x 250 USD or $850,000. The E-mini S-P 500 futures contract is 50 times higher than the index. If the index is trading at 3400 points, the market value of the contract would be 3,400 x 50 usd or $170,000. The results are shown in the maps in Figure 5. All maps show the expected patterns of concordance over time: areas where the NDVI signal is highly dynamic, such as the northern production areas, are more consistent than desert areas, where the signal is mainly audible. However, there is a big difference where each metric provides negative values: the map does not display negative values, the Watterson M metric map only takes negative values when the correlation is negative, but the map of the Ji-Gallo AC index shows huge areas of negative values throughout the territory. The comparison between b and r reflects the added value of using the former, which includes distortions that do not exist in the latter. The extent of these distortions in relation to global deviations can be interconnected in the map, while datasets compliance is displayed in the map regardless of these distortions.
Systematic additive and proportional distortions can interact. To illustrate this situation, column c) in Figure 2 shows the value between the index calculated for 2 vectors, with a given combination of distortions minus the value of the index calculated from the same vectors without bias. This only appears for a given correlation of. This graphical representation can help illustrate the sensitivity of an index for small changes in b and m. Most indices react in the same way, with the notable exception of HQ. The AC Ji-Gallo index may be higher (i.e. more compliance) with a combination of small distortions than without any bias. Legates, D. R.
– McCabe, G. J. A refined index of the model`s performance: a counter-response. International Journal of Climatology 33, 1053-1056. Limited between a lower limit (z.B. 0) that does not correspond to any agreement and a ceiling (for example. B 1) A perfect match. One consequence is that higher values should always indicate greater agreement. Another common approach is to take into account that a statistical model can be adapted to the data.