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All the observation distributions are degenerate i.e. a single output can be observed in a state except the observation distribution for the Markovian state B with a mixture of primordia and emerged roots.
As before, the basic models used are HMMs that employ Gaussian mixtures to represent the state observation distributions.
When there is a sufficient number of hidden states with a rich class of observation distributions, the HMMs can accurately represent probability distributions in complex real world problems and create simple and compact models [34].
To a first approximation, the transformation applied to model data corrects the model distribution for bias and spread with respect to observation distributions.
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The model is characterised by the observation distribution, the transition distribution, and the initial state distribution.
Broad and uniform observation distribution would be also favorable for good forecasting.
The observation distribution of the ships (Fig. 3b) is broader and more uniform than that of the deep-sea pressure and GPS buoy observations (Fig. 3a).
Tables 1, 2, and 3 shows the initial state probabilities distribution, observation distribution, and transition probabilities respectively for each VM in the vCell.
HMEM improves both state duration distribution p i ∙ i = 1 N and output observation distribution b i ∙ i = 1 N using maximum entropy modeling.
The bottom panel of Fig. 3 shows the GPS observation distribution of Swarm-A and Swarm-C for the time period from 26 January to 3 March 2015.
Thus, the output of our algorithm may mistake the undesired objects for the desired one because of the inaccurate adopted observation distribution.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com