MorphIQ Markov / Hidden-state inference
Hidden states. Observable evidence.
Hidden-state modeling, filtering, smoothing and parameter estimation for time series—with explicit convergence and numerical diagnostics.
- Current and retrospective estimates
- Filter + smooth
- Latent structure in time series
- Hidden states
- Convergence and numerical behavior
- Diagnostics
Capabilities
A focused responsibility. A clear interface.
Estimate hidden state
Model the latent structure behind a sequence of observations.
Filter and smooth
Distinguish estimates using information available now from retrospective estimates using the full sequence.
Inspect the fit
Keep convergence and numerical diagnostics visible when estimating parameters.
Explore the family
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Correctly rounded core functions, machine-checked error bounds and SIMD kernels that preserve scalar results across supported platforms.