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# Manual
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+ For a concise overview of the package, please read the [ package paper] ( https://arxiv.org/abs/2008.05506 ) .
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+ It provides a high-level presentation of the theory behind score-driven models and showcases the features of the package as well as examples.
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## Model Specification
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``` @docs
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The constructor of a score-driven model. The model receives the lag structure, the
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distribution and the scaling. You can define the lag structure in two different
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- ways, either by passing integers `p` and `q` to add all lags from `1` to `p and `1` to `q` or by
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+ ways, either by passing integers `p` and `q` to add all lags from `1` to `p` and `1` to `q` or by
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passing vectors of integers `ps` and `qs` containing the desired lags. Once you build
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the model all of the unknown parameters that must be estimated are represented as `NaN`.
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