TEMPoral TEnsor Decomposition (TEMPTED), is a dimension reduction method for multivariate longitudinal data with varying temporal sampling. It formats the data into a temporal tensor and decomposes it into a summation of low-dimensional components, each consisting of a subject loading vector, a feature loading vector, and a continuous temporal loading function. These loadings provide a low-dimensional representation of subjects or samples and can be used to identify features associated with clusters of subjects or samples. TEMPTED provides the flexibility of allowing subjects to have different temporal sampling, so time points do not need to be binned, and missing time points do not need to be imputed.

Implementation of ZENIT-POLAR substitution cipher method of encryption using by default the TENIS-POLAR cipher. This last cipher of encryption became famous through the collection of Brazilian books "Os Karas" by the author Pedro Bandeira. For more details, see "A Cryptographic Dictionary" (GC&CS, 1944).

Implements methods and functions to calibrate 
  time-specific niche models (multi-temporal calibration), letting users 
  execute a strict calibration and selection process of niche models based 
  on ellipsoids, as well as functions to project the potential distribution in 
  the present and in global change  scenarios.The 'tenm' package has functions
  to recover information that may be lost or overlooked while applying a data 
  curation protocol. This curation involves preserving occurrences that may 
  appear spatially redundant (occurring in the same pixel) but originate from 
  different time periods. A novel aspect of this package is that it might 
  reconstruct the fundamental niche more accurately than mono-calibrated 
  approaches. The theoretical background of the package can be found in 
  Peterson et al. (2011)<doi:10.5860/CHOICE.49-6266>.

The tensor product of two arrays is notionally an outer
        product of the arrays collapsed in specific extents by summing
        along the appropriate diagonals.