Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The mbsts package: Multivariate Bayesian Structural Time Series Models
  in R   The multivariate Bayesian structural time series (MBSTS) model
\citep{qiu2018multivariate,Jammalamadaka2019Predicting} as a generalized
version of many structural time series models, deals with inference and
prediction for multiple correlated time series, where one also has the choice
of using a different candidate pool of contemporaneous predictors for each
target series. The MBSTS model has wide applications and is ideal for feature
selection, time series forecasting, nowcasting, inferring causal impact, and
others. This paper demonstrates how to use the R package \pkg{mbsts} for MBSTS
modeling, establishing a bridge between user-friendly and developer-friendly
functions in package and the corresponding methodology. A simulated dataset and
object-oriented functions in the \pkg{mbsts} package are explained in the way
that enables users to flexibly add or deduct some components, as well as to
simplify or complicate some settings.

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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: nlin
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The categories of this paper are: econ
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The categories of this paper are: physics
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The categories of this paper are: chem-ph
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
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The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
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The categories of this paper are: cond-mat
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The categories of this paper are: q-bio
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The categories of this paper are: cmp-lg
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The categories of this paper are: acc-phys
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The categories of this paper are: q-fin
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The categories of this paper are: plasm-ph