Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: R package imputeTestbench to compare imputations methods for univariate
  time series   This paper describes the R package imputeTestbench that provides a testbench
for comparing imputation methods for missing data in univariate time series.
The imputeTestbench package can be used to simulate the amount and type of
missing data in a complete dataset and compare filled data using different
imputation methods. The user has the option to simulate missing data by
removing observations completely at random or in blocks of different sizes.
Several default imputation methods are included with the package, including
historical means, linear interpolation, and last observation carried forward.
The testbench is not limited to the default functions and users can add or
remove additional methods using a simple two-step process. The testbench
compares the actual missing and imputed data for each method with different
error metrics, including RMSE, MAE, and MAPE. Alternative error metrics can
also be supplied by the user. The simplicity of use and significant reduction
in time to compare imputation methods for missing data in univariate time
series is a significant advantage of the package. This paper provides an
overview of the core functions, including a demonstration with examples.

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The categories of this paper are: astro-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: funct-an
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The categories of this paper are: adap-org
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: bayes-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: math
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
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The categories of this paper are: math-ph
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The categories of this paper are: patt-sol
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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: ao-sci