hmmtmb
Fit hidden Markov models using Template Model Builder (TMB): flexible state-dependent distributions, transition probability structures, random effects, and smoothing splines.
Science Score: 59.0%
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Low similarity (15.4%) to scientific vocabulary
Keywords
Repository
Fit hidden Markov models using Template Model Builder (TMB): flexible state-dependent distributions, transition probability structures, random effects, and smoothing splines.
Basic Info
Statistics
- Stars: 56
- Watchers: 8
- Forks: 9
- Open Issues: 4
- Releases: 0
Topics
Metadata Files
README.md
hmmTMB
This R package implements flexible hidden Markov models, based on Template Model Builder (TMB): flexible state-dependent distributions, transition probability structures, random effects, and smoothing splines.
Preprint
The statistical background, as well as details about the implementation of the package, and several example analyses, are presented in the following preprint.
Package installation
The package is available on CRAN, and the stable version can therefore be installed using
install.packages("hmmTMB")
The development version of the package can be installed from Github using devtools,
devtools::install_github("TheoMichelot/hmmTMB")
Package documentation
To find help files for the methods implemented in the package, search for help using the name of the corresponding class, e.g.,
?MarkovChain
?Observation
?HMM
We describe functionalities of the package in several vignettes, which are listed below.
Main vignette
- 'Analysing time series data with hidden Markov models in hmmTMB': Overview of package workflow, using detailed example based on analysis of energy prices. This is a good starting point to learn how to use the package.
Other features
'Bayesian inference in hmmTMB': Description of workflow for Bayesian analysis in hmmTMB, including specifying priors, and extracting posterior samples.
'Advanced features of hmmTMB': Description of some other useful functionalities, including (semi-)supervised learning, parameter constraints, selection of initial parameter values, etc.
'General dependence structures in hmmTMB': Implementation details for hidden Markov models (HMMs) with non-standard dependence structures, including hidden semi-Markov models, higher-order HMMs, autoregressive HMMs, and coupled HMMs.
Case studies
'Flexible animal movement modelling using hmmTMB': Description of wild haggis movement analysis, illustrating how non-parametric covariate effects can be included. This includes two different types of movement models: (1) correlated random walks based on step lengths and turning angles, and (2) correlated random walks based on locations directly.
'Occupancy modelling using hmmTMB': Analysis of occupancy data set of crossbill from Kéry et al. (2013).
'The categorical distribution in hmmTMB': The categorical distribution is slightly different from others, in that the number of parameters depends on the data (specifically, on the number of categories in the data). This vignette shows an example analysis for a data set on patient-therapist interactions from the mHMMbayes package.
- 'The multivariate normal distribution in hmmTMB': We illustrate the state-dependent multivariate normal distribution for modelling correlated variables, using time series of log-returns. The vignette describes the formulation in terms of standard deviations and correlation parameters, and compares this approach to using multiple univariate normal distributions.
Reference vignettes
'List of distributions in hmmTMB': List of observation distributions currently available in hmmTMB.
'Adding new distributions in hmmTMB': Technical vignette about adding new observation distributions to hmmTMB, with detailed instructions to add the required R and C++ code.
'Syntax of model formulas in hmmTMB': Flexible covariate dependence can be specified using the syntax of mgcv formulas, and this vignette describes a few special cases, including random effects (intercepts or slopes), smooth non-linear relationships, factor-smooth interactions, multidimensional smooths, varying-coefficient models, cyclical effects, etc.
'HMM package comparison': Comparison of syntax between several R packages (hmmTMB, momentuHMM, depmixS4, LMest) and a Python package (hmmlearn) for a simple 2-state Gaussian HMM.
Owner
- Name: Théo Michelot
- Login: TheoMichelot
- Kind: user
- Location: Halifax
- Company: Dalhousie University
- Website: https://theomichelot.github.io/
- Twitter: TheoMichelot
- Repositories: 3
- Profile: https://github.com/TheoMichelot
Assistant professor in statistics at Dalhousie University, Halifax, Canada
GitHub Events
Total
- Issues event: 2
- Watch event: 4
- Push event: 17
- Pull request event: 1
- Pull request review event: 2
- Pull request review comment event: 1
- Fork event: 2
- Create event: 1
Last Year
- Issues event: 2
- Watch event: 4
- Push event: 17
- Pull request event: 1
- Pull request review event: 2
- Pull request review comment event: 1
- Fork event: 2
- Create event: 1
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 714
- Total Committers: 4
- Avg Commits per committer: 178.5
- Development Distribution Score (DDS): 0.588
Top Committers
| Name | Commits | |
|---|---|---|
| Théo Michelot | t****5@s****k | 294 |
| Theo Michelot | t****t@g****m | 272 |
| richard | g****e@g****k | 147 |
| Brett McClintock | b****k@u****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 22
- Total pull requests: 2
- Average time to close issues: 3 months
- Average time to close pull requests: about 20 hours
- Total issue authors: 5
- Total pull request authors: 2
- Average comments per issue: 1.91
- Average comments per pull request: 0.5
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- TheoMichelot (11)
- r-glennie (5)
- roaldarbol (4)
- orijitghosh (1)
- Beliavsky (1)
- RonEfrat (1)
Pull Request Authors
- DuncanCSt (2)
- bmcclintock (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- cran 351 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 4
- Total maintainers: 1
cran.r-project.org: hmmTMB
Fit Hidden Markov Models using Template Model Builder
- Homepage: https://github.com/TheoMichelot/hmmTMB
- Documentation: http://cran.r-project.org/web/packages/hmmTMB/hmmTMB.pdf
- License: GPL-3
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Latest release: 1.1.0
published 8 months ago
Rankings
Maintainers (1)
Dependencies
- R6 * depends
- RcppEigen * depends
- TMB * depends
- ggplot2 * depends
- mgcv * depends
- Matrix * imports
- optimx * imports
- stringr * imports
- CircStats * suggests
- rstan * suggests
- testthat * suggests
- tmbstan * suggests