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Structural Bayesian Information Criterion for Graphical Models
This is the implementation of the novel structural Bayesian information criterion by Zhou, 2020 (under review). In this method, the prior structure is modeled and incorporated into the Bayesian information criterion framework. Additionally, we also provide the implementation of a two-step algorithm to generate the candidate model pool.
R Interface to 'EPP-Lab', a Java Program for Exploratory Projection Pursuit
An R Interface to 'EPP-lab' v1.0. 'EPP-lab' is a Java program for projection pursuit using genetic algorithms written by Alain Berro and S. Larabi Marie-Sainte and is included in the package.
Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering
Contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models. The package is primarily related to the publications Komárek (2009, Comp. Stat. and Data Anal.)
Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples
Methods for obtaining improved estimates of non-linear cross-validated risks are obtained using targeted minimum loss-based estimation, estimating equations, and one-step estimation (Benkeser, Petersen, van der Laan (2019),
Spatial Ecology Miscellaneous Methods
Collection of R functions and data sets for the support of spatial ecology analyses with a focus on pre, core and post modelling analyses of species distribution, niche quantification and community assembly. Written by current and former members and collaborators of the ecospat group of Antoine Guisan, Department of Ecology and Evolution (DEE) and Institute of Earth Surface Dynamics (IDYST), University of Lausanne, Switzerland. Read Di Cola et al. (2016)
Continuous Mapping of Genetic Diversity
Generate continuous maps of genetic diversity using moving windows with options for rarefaction, interpolation, and masking as described in Bishop et al. (2023)
Time Series Artificial Neural Network
The best ANN structure for time series data analysis is a demanding need in the present era.
This package will find the best-fitted ANN model based on forecasting accuracy.
The optimum size of the hidden layers was also determined after determining the number of lags to be included.
This package has been developed using the algorithm of Paul and Garai (2021)
Estimation of Transmissibility in the Early Stages of a Disease Outbreak
Implements a simple, likelihood-based estimation of the reproduction number (R0) using a branching process with a Poisson likelihood. This model requires knowledge of the serial interval distribution, and dates of symptom onsets. Infectiousness is determined by weighting R0 by the probability mass function of the serial interval on the corresponding day. It is a simplified version of the model introduced by Cori et al. (2013)
ICS via a Shiny Application
Performs Invariant Coordinate Selection (ICS) (Tyler, Critchley, Duembgen and Oja (2009)
Dynamic Model of Ammonia Emission from Field-Applied Manure
An implementation of the ALFAM2 dynamic emission model for ammonia volatilization from field-applied animal slurry (manure with dry matter below about 15%). The model can be used to predict cumulative emission and emission rate of ammonia following field application of slurry. Predictions may be useful for emission inventory calculations, fertilizer management, assessment of mitigation strategies, or research aimed at understanding ammonia emission. Default parameter sets include effects of application method, slurry composition, and weather. The model structure is based on a simplified representation of the physical-chemical slurry-soil-atmosphere system. See Hafner et al. (2018)