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Also, note that 5) implies that any strongly time consistent dynamic LM-measure can be constructed using a backward recursion starting from φ T :=ϱ, where ϱ is an LM-measure.
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Model simplification was performed using a backward stepwise algorithm.
These covariates were selected using a backward stepwise procedure.
The model was optimized using a backward stepwise regression.
Prognostic factors were identified using a backward selection procedure.
Variables were selected using a backward stepwise process.
Non-significant predictors were eliminated using a backward elimination method.
The forward algorithm and the backward algorithm, which is analogous to the forward algorithm but differs in that a backward recursion starts at the end of a sequence, can compute the probability of a sequence given an HMM by dynamic programming with the same running time of the Viterbi algorithm.
The transformation uses a backward mapping with bilinear interpolation.
We used a backward stepwise approach.
We used a backward selection procedure to identify significant confounders.
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