Uncovering ecological state dynamics with hidden Markov models

BT McClintock, R Langrock, O Gimenez, E Cam… - Ecology …, 2020 - Wiley Online Library
Ecological systems can often be characterised by changes among a finite set of underlying
states pertaining to individuals, populations, communities or entire ecosystems through time …

Joint latent class models for longitudinal and time-to-event data: a review

C Proust-Lima, M Séne, JMG Taylor… - … methods in medical …, 2014 - journals.sagepub.com
Most statistical developments in the joint modelling area have focused on the shared
random-effect models that include characteristics of the longitudinal marker as predictors in …

[图书][B] Model-based clustering and classification for data science: with applications in R

C Bouveyron, G Celeux, TB Murphy, AE Raftery - 2019 - books.google.com
Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …

[图书][B] Principles of system identification: theory and practice

AK Tangirala - 2018 - taylorfrancis.com
Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-
driven or measurement-based process operations, system identification is an interface that …

Estimation of extended mixed models using latent classes and latent processes: the R package lcmm

C Proust-Lima, V Philipps, B Liquet - arXiv preprint arXiv:1503.00890, 2015 - arxiv.org
The R package lcmm provides a series of functions to estimate statistical models based on
linear mixed model theory. It includes the estimation of mixed models and latent class mixed …

[图书][B] Mixture model-based classification

PD McNicholas - 2016 - taylorfrancis.com
" This is a great overview of the field of model-based clustering and classification by one of
its leading developers. McNicholas provides a resource that I am certain will be used by …

[HTML][HTML] Model-based clustering

PD McNicholas - Journal of Classification, 2016 - Springer
The notion of defining a cluster as a component in a mixture model was put forth by
Tiedeman in 1955; since then, the use of mixture models for clustering has grown into an …

[图书][B] Finite mixture and Markov switching models

S Frühwirth-Schnatter - 2006 - Springer
Modelling based on finite mixture distributions is a rapidly developing area with the range of
applications exploding. Finite mixture models are nowadays applied in such diverse areas …

[HTML][HTML] An approach for determining the number of clusters in a model-based cluster analysis

S Akogul, M Erisoglu - Entropy, 2017 - mdpi.com
To determine the number of clusters in the clustering analysis that has a broad range of
applied sciences, such as physics, chemistry, biology, engineering, economics etc., many …

Local solutions in the estimation of growth mixture models.

JR Hipp, DJ Bauer - Psychological methods, 2006 - psycnet.apa.org
Finite mixture models are well known to have poorly behaved likelihood functions featuring
singularities and multiple optima. Growth mixture models may suffer from fewer of these …