QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
RcppArmadillo: Accelerating R with high-performance C++ linear algebra
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Proposes adaptive and alternative algorithms to improve the computational efficiency of simulation smoothing for large mixed-frequency VARs in nowcasting applications.
iglm is an R package that implements scalable regression for outcomes under interference in connected populations using pseudo-likelihood optimization with theoretical guarantees.
citing papers explorer
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Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models
QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
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Simulation smoothing for nowcasting with large mixed-frequency VARs
Proposes adaptive and alternative algorithms to improve the computational efficiency of simulation smoothing for large mixed-frequency VARs in nowcasting applications.
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R Package iglm: Regression under Interference in Connected Populations
iglm is an R package that implements scalable regression for outcomes under interference in connected populations using pseudo-likelihood optimization with theoretical guarantees.