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Very briefly, the process includes i) observations (such as the fossil record) and experimental data (e.g., DNA sequences).

Firstly, there is the number of cases in which n vectors are selected from k ~ i observations obtained from the i th radar.

This procedure was equivalent to sort X p and Y i observations and discarded 10% of the smallest and 10% of the largest values from each one.

Suppose a grid contains k squares, with the ith square containing n i observations with ( {sum}_{i=1}^k{n}_i=N ).

For this purpose, we compared models established within a model-based framework, where inference is derived from the assumption that the y i observations of AGB are considered realizations of the random variable Y i, which in turn are realizations of a random process termed a superpopulation (Gregoire 1998; Ståhl et al. 2016).

The design-based estimate assumes that the population of Y i is fixed, not random, while the sample of y i observations is the realization of a random process, and inference is independent from assumptions regarding the probability distribution of Y i in the population (Gregoire 1998; Ståhl et al. 2016).

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The subscript − ij in y − ij denotes that for patient i observation j is removed.

As previous reports on such molecular ions are insufficient (Klecker et al. 1986; Yau et al. 1993; Peterson et al. 1994), it is expected that MEP-i observations will provide more information regarding molecular ion behaviors (e.g., dependence on L-value, magnetic local time, and solar activity) to reveal the escaping mechanisms of the Earth's atmospheric particles.

Using our metabolic model we first try to understand observation (i) taking observation (ii) into account.

Letting (O_i) denote the hour-i observation, the SP forecast of the hour-((i+Delta i)) weather variable generated at hour i is defined as (O_i).

The observed intensity I h (i) for observation i of Miller index h is a thin slice through a three-dimensional reflection.

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