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## Solution
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Stationary bootstrap is a block-resampling technique that relaxes the assumption in a classical bootstrap where the sampling block has a fixed-length. The user still needs to specify an average length, but because this is than taken as a statistical average, shorter/longer blocks are also present in the final sample.
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Stationary bootstrap is a block-resampling technique that relaxes the assumption in a classical bootstrap where the sampling block has a fixed-length. The user still needs to specify an average length, but because this is than applied as a statistical average, shorter/longer blocks are also present in the final sample.
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The algorithm works by randomly selecting a starting point in the time-series and at each step it either increases the block size by one or selects a new block with a new starting point. This choice happens with a fixed probability governed by the parametrisation.
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### Input

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