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We introduce a new characterization of the Cauchy distribution and propose a class of goodness-of-fit tests for the Cauchy family. The limit distribution is derived in a Hilbert space framework under the null hypothesis. The new tests are consistent against a large class of alternatives. A...
Persistent link: https://www.econbiz.de/10015179567
We offer a new and straightforward proof of F.B. Knight's [3] theorem that the Cauchy type is characterized by the fact that it has no atom and is invariant under the involution i : x - -1/x. Our approach uses the representation X = tan theta where theta is uniform on (-pi/2,pi/2) when X is...
Persistent link: https://www.econbiz.de/10005762834
A limit theory is developed for mildly explosive autoregression under both weakly and strongly dependent innovation errors. We find that the asymptotic behaviour of the sample moments is affected by the memory of the innovation process both in the in the form of the limiting distribution and, in...
Persistent link: https://www.econbiz.de/10008497826
A limit theory is developed for the least squares estimator for mildly and purely explosive autoregressions under drifting sequences of parameters with autoregressive roots ρn satisfying ρn Ç ρ ∈ (-É, -1] ∪ [1, É) and n (
Persistent link: https://www.econbiz.de/10015054281
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A limit theory is developed for the least squares estimator for mildly and purely explosive autoregressions under drifting sequences of parameters with autoregressive roots ρn satisfying ρn → ρ ∈ (-∞, -1] ∪ [1, ∞) and n (|ρn| -1) → ∞. Drifting sequences of innovations and...
Persistent link: https://www.econbiz.de/10015051928
We introduce a new characterization of the Cauchy distribution and propose a class of goodness-of-fit tests for the Cauchy family. The limit distribution is derived in a Hilbert space framework under the null hypothesis. The new tests are consistent against a large class of alternatives. A...
Persistent link: https://www.econbiz.de/10015407833
The energy consumption of large-scale data centers or server clusters is expected to grow significantly in the next couple of years contributing to up to 13% of the worldwide energy demand in 2030. As the involved processing units require a disproportional amount of energy when they are idle,...
Persistent link: https://www.econbiz.de/10014501961