Multivariate two-sample tests based on K-nearest-neighbors
Peng Dai <peng.dai@stonybrook.edu> and Wei Dou
<wei.dou@yale.edu>
The package contains three multivariate two-sample tests
which are all based on k-nearest-neighbors. The testing
procedures are distribution free and are robust from balanced
designs to unbalanced designs.

Lisha Chen <lisha.chen@yale.edu>, Peng Dai
<peng.dai@stonybrook.edu> and Wei Dou <wei.dou@yale.edu>
The package contains four multivariate two-sample tests
which are all based on k-nearest-neighbors. The testing
procedures are distribution free and are robust from balanced
designs to unbalanced designs.

Methods in Mahalanobis-Taguchi (MT) System
c(
person("Akifumi", "Okayama", email = "akifumi.okayama@akane.waseda.jp",
role = c("aut", "cre")),
person("Masato", "Ohkubo", role = "ctb"),
person("Yasushi", "Nagata", role = "ctb"))
Mahalanobis-Taguchi (MT) system is a collection of multivariate
analysis methods developed for the field of quality engineering. MT system
consists of two families depending on their purpose. One is a family of
Mahalanobis-Taguchi (MT) methods (in the broad sense) for diagnosis (see
Woodall, W. H., Koudelik, R., Tsui, K. L., Kim, S. B., Stoumbos, Z. G., and
Carvounis, C. P. (2003) <doi:10.1198/004017002188618626>) and the other is a
family of Taguchi (T) methods for forecasting (see Kawada, H., and Nagata, Y.
(2015) <doi:10.17929/tqs.1.12>). The MT package contains three basic methods
for the family of MT methods and one basic method for the family of T
methods. The MT method (in the narrow sense), the Mahalanobis-Taguchi
Adjoint (MTA) methods, and the Recognition-Taguchi (RT) method are for the
MT method and the two-sided Taguchi (T1) method is for the family of T
methods. In addition, the Ta and Tb methods, which are the improved versions
of the T1 method, are included.
Akifumi Okayama [aut, cre],
Masato Ohkubo [ctb],
Yasushi Nagata [ctb]

Access to Amazon Mechanical Turk Requester API
This package provides access to the Amazon Mechanical Turk
(MTurk) Requester API via authenticated HTTP requests executed
with the RCurl package and a number of functions to translate
API calls into R data structures (using the XML package).