Functions required for the 'SciViews::R' dialect or for general
  use: manage a temporary environment attached to the search path, define
  synonyms for R functions using aka(), test if 'Aqua', 'Mac', 'Win' ... Show
  progress bar, etc.

Implements the SVM-Maj algorithm to train data with support vector machine
  <doi:10.1007/s11634-008-0020-9>.
  This algorithm uses two efficient updates, one for linear kernel and one 
  for the nonlinear kernel.

Computes the entire regularization path for the two-class svm classifier
		with essentially the same cost as a single SVM fit.

Determines networks of significant synchronization between the discrete states of nodes; see Tumminello et al <doi:10.1371/journal.pone.0017994>.

Two versions of sample variance plots, Sv-plot1 and Sv-plot2, will be provided illustrating 
             the squared deviations from sample variance. Besides indicating the contribution of squared 
             deviations for the sample variability, these plots are capable of detecting characteristics of the
             distribution such as symmetry, skewness and outliers. A remarkable graphical method based on 
             Sv-plot2 can determine the decision on testing hypotheses over one or two population means. 
             In sum, Sv-plots will be appealing visualization tools. Complete description of this methodology  
             can be found in the article, Wijesuriya (2020) <doi:10.1080/03610918.2020.1851716>.

Provides tools for creating and working with survey replicate weights,
  extending functionality of the 'survey' package from Lumley (2004) <doi:10.18637/jss.v009.i08>.
  Implements bootstrap methods for complex surveys, including the generalized survey bootstrap
  as described by Beaumont and Patak (2012) <doi:10.1111/j.1751-5823.2011.00166.x>.
  Methods are provided for applying nonresponse adjustments to
  both full-sample and replicate weights as described by 
  Rust and Rao (1996) <doi:10.1177/096228029600500305>.
  Implements methods for sample-based calibration described by Opsomer and Erciulescu (2021) 
  <https://www150.statcan.gc.ca/n1/pub/12-001-x/2021002/article/00006-eng.htm>.
  Diagnostic functions are included to compare weights and weighted estimates
  from different sets of replicate weights.