Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Non-Gaussian Autoregressive Processes with Tukey g-and-h Transformations   When performing a time series analysis of continuous data, for example from
climate or environmental problems, the assumption that the process is Gaussian
is often violated. Therefore, we introduce two non-Gaussian autoregressive time
series models that are able to fit skewed and heavy-tailed time series data.
Our two models are based on the Tukey g-and-h transformation. We discuss
parameter estimation, order selection, and forecasting procedures for our
models and examine their performances in a simulation study. We demonstrate the
usefulness of our models by applying them to two sets of wind speed data.

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The categories of this paper are: gr-qc
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The categories of this paper are: dg-ga
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The categories of this paper are: mtrl-th
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: math
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The categories of this paper are: hep-th
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The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
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The categories of this paper are: atom-ph
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The categories of this paper are: q-fin
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The categories of this paper are: q-alg
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The categories of this paper are: astro-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: cond-mat
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The categories of this paper are: physics