Abstract:Online changepoint detection algorithms that are based on likelihood-ratio tests have been shown to have excellent statistical properties. However, a simple online implementation is computationally infeasible as, at time T , it involves considering O(T ) possible locations for the change. Recently, the FOCuS algorithm has been introduced for detecting changes in mean in Gaussian data that decreases the per-iteration cost to O(log T ). This is possible by using pruning ideas, which reduce the set of changepoint… Show more
“…), being unimodal. Similar results apply for other functions, and these have been used to generalise the FOCuS algorithm to other one-parameter exponential family models (see Ward et al, 2023).…”
Section: Step 2: Efficient Pruning Of the Bernoulli Costmentioning
“…), being unimodal. Similar results apply for other functions, and these have been used to generalise the FOCuS algorithm to other one-parameter exponential family models (see Ward et al, 2023).…”
Section: Step 2: Efficient Pruning Of the Bernoulli Costmentioning
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