A 2-Dimensional Functional Central Limit Theorem for Non-stationary Dependent Random Fields
Abstract
We obtain an elementary invariance principle for multi-dimensional Brownian sheet where the underlying random fields are not necessarily independent or stationary. Possible applications include unit-root tests for spatial as well as panel data models.
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