An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed hydrological model originally proposed by Beven and Freer (2001) <doi:10.1002/hyp.252>. The 'dynatop' package implements code for simulating models which can be created using the 'dynatopGIS' package.

A set of algorithms based on Quinn et al. (1991) <doi:10.1002/hyp.3360050106> for processing river network and digital elevation data to build implementations of Dynamic TOPMODEL, a semi-distributed hydrological model proposed in Beven and Freer (2001) <doi:10.1002/hyp.252>. The 'dynatop' package implements simulation code for Dynamic TOPMODEL based on the output of 'dynatopGIS'.

Inference by sequential Monte Carlo for 
  dynamic tree regression and classification models
  with hooks provided for sequential design and optimization, 
  fully online learning with drift, variable selection, and 
  sensitivity analysis of inputs.  Illustrative 
  examples from the original dynamic trees paper 
  (Gramacy, Taddy & Polson (2011); <doi:10.1198/jasa.2011.ap09769>) are facilitated
  by demos in the package; see demo(package="dynaTree").

A GUI to solve dynamic biplots and classical biplot. Try matrices
    of 2-way and 3-way. The GUI can be run in multiple languages.

A two-stage procedure for the denoising and clustering of stack of noisy images acquired over time. Clustering only assumes that the data contain an unknown but small number of dynamic features. The method first denoises the signals using local spatial and full temporal information. The clustering step uses the previous output to aggregate voxels based on the knowledge of their spatial neighborhood. Both steps use a single keytool based on the statistical comparison of the difference of two signals with the null signal. No assumption is therefore required on the shape of the signals. The data are assumed to be normally distributed (or at least follow a symmetric distribution) with a known constant variance. Working pixelwise, the method can be time-consuming depending on the size of the data-array but harnesses the power of multicore cpus.