Stability with respect to initial conditions in V-norm for nonlinear filters with ergodic observations
2017 ◽
Vol 54
(1)
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pp. 118-133
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Keyword(s):
AbstractWe establish conditions for an exponential rate of forgetting of the initial distribution of nonlinear filters in V-norm, allowing for unbounded test functions. The analysis is conducted in an general setup involving nonnegative kernels in a random environment which allows treatment of filters and prediction filters in a single framework. The main result is illustrated on two examples, the first showing that a total variation norm stability result obtained by Douc et al. (2009) can be extended to V-norm without any additional assumptions, the second concerning a situation in which forgetting of the initial condition holds in V-norm for the filters, but the V-norm of each prediction filter is infinite.
2014 ◽
Vol 51
(3)
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pp. 756-768
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2014 ◽
Vol 51
(03)
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pp. 756-768
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Keyword(s):
2021 ◽
Vol 3
(2)
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pp. 1-15
Keyword(s):
2021 ◽