Estimating finite mixtures of semi‐Markov chains: an application to the segmentation of temporal sensory data. Issue 5 (28th May 2019)
- Record Type:
- Journal Article
- Title:
- Estimating finite mixtures of semi‐Markov chains: an application to the segmentation of temporal sensory data. Issue 5 (28th May 2019)
- Main Title:
- Estimating finite mixtures of semi‐Markov chains: an application to the segmentation of temporal sensory data
- Authors:
- Cardot, Hervé
Lecuelle, Guillaume
Schlich, Pascal
Visalli, Michel - Abstract:
- Summary: In food science, it is of great interest to obtain information about the temporal perception of aliments to create new products, to modify existing products or more generally to understand the mechanisms of perception. Temporal dominance of sensations is a technique to measure temporal perception which consists in choosing sequentially attributes describing a food product over tasting. This work introduces new statistical models based on finite mixtures of semi‐Markov chains to describe data collected with the temporal dominance of sensations protocol, allowing different temporal perceptions for a same product within a population. The identifiability of the parameters of such mixture models is discussed. Sojourn time distributions are fitted with a gamma probability distribution and a penalty is added to the log‐likelihood to ensure convergence of the expectation–maximization algorithm to a non‐degenerate solution. Information criteria are employed for determining the number of mixture components. Then, the individual qualitative trajectories are clustered with the help of the maximum a posteriori probability approach. A simulation study confirms the good behaviour of the estimation procedure proposed. The methodology is illustrated on an example of consumers' perception of a Gouda cheese and assesses the existence of several behaviours in terms of perception of this product.
- Is Part Of:
- Journal of the Royal Statistical Society. Volume 68:Issue 5(2019)
- Journal:
- Journal of the Royal Statistical Society
- Issue:
- Volume 68:Issue 5(2019)
- Issue Display:
- Volume 68, Issue 5 (2019)
- Year:
- 2019
- Volume:
- 68
- Issue:
- 5
- Issue Sort Value:
- 2019-0068-0005-0000
- Page Start:
- 1281
- Page End:
- 1303
- Publication Date:
- 2019-05-28
- Subjects:
- Bayesian information criterion -- Categorical time series -- Expectation–maximization algorithm -- Gamma distribution -- Identifiability -- Markov renewal process -- Model‐based clustering -- Penalized likelihood -- Temporal dominance of sensations
Statistics -- Periodicals
519.5 - Journal URLs:
- http://rss.onlinelibrary.wiley.com/hub/journal/10.1111/(ISSN)1467-9876/ ↗
https://academic.oup.com/jrsssc ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/rssc.12356 ↗
- Languages:
- English
- ISSNs:
- 0035-9254
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1580.000000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 17313.xml