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A Multivariate Hidden SemiMarkov Model of Customer Multichannel Engagement Sharpish Sitar Tuck School of Business, Dartmouth College, 210 Tuck Hall, Hanover NH 03755, sharmistha.sikdar@tuck.dartmouth.edu

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How to fill out a multivariate hidden semi-markov

01

Define the states and observations for each variable in the multivariate hidden semi-markov model.

02

Specify the transition probabilities between states for each variable.

03

Determine the emission probabilities for each observation based on the hidden states.

04

Initialize the model parameters such as initial state probabilities and duration distributions.

05

Use an algorithm such as the Baum-Welch algorithm to estimate the model parameters based on the observed data.

06

Validate the model by comparing the predicted sequences against the actual sequences.

Who needs a multivariate hidden semi-markov?

01

Researchers in fields such as speech recognition, bioinformatics, and financial modeling who need to analyze sequential data with hidden states and multiple variables.

02

Companies developing predictive maintenance systems or anomaly detection algorithms that require modeling complex relationships between variables.

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What is a multivariate hidden semi-markov?

A multivariate hidden semi-markov is a statistical model that extends the traditional hidden Markov model to include multiple variables.

Who is required to file a multivariate hidden semi-markov?

Researchers and analysts who are working with complex time series data may be required to utilize a multivariate hidden semi-markov.

How to fill out a multivariate hidden semi-markov?

To fill out a multivariate hidden semi-markov, one must define the states, transition probabilities, observation probabilities, and emission probabilities for each variable.

What is the purpose of a multivariate hidden semi-markov?

The purpose of a multivariate hidden semi-markov is to model complex relationships in sequential data where multiple variables interact with each other.

What information must be reported on a multivariate hidden semi-markov?

On a multivariate hidden semi-markov, one must report the states, transition probabilities, observation probabilities, emission probabilities, and the relationships between variables.

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