tcltk, tkrplot, foreach, doParallel, parallel

Author: Leopoldo Catania & Mauro Bernardi
Description: Perform the model confidence set procedure of Hansen et al (2011).
Packaged: 2014-11-18 11:00:54 UTC; Leopoldo Catania

Packaged: 2015-03-22 19:15:19 UTC; Leopoldo Catania

Description: Perform the model confidence set procedure of Hansen et al (2011) <doi:10.3982/ECTA5771>.

Title: Determine the Optimal Number of Clusters
Author: Ahmed N. Albatineh, Meredith L. Wilcox, Bashar Zogheib, Magdalena Niewiadomska-Bugaj
Maintainer: Ahmed N. Albatineh <aalbatineh@hsc.edu.kw>
Description: Identifies the optimal number of clusters by calculating the similarity between
two clustering methods at the same number of clusters using the corrected indices of Rand and
Jaccard as described in Albatineh and Niewiadomska-Bugaj (2011). The number of clusters at
which the index attain its maximum more frequently is a candidate for being the optimal
Packaged: 2018-10-08 10:37:50 UTC; aalbatineh

Title: Markov Chains Transition Matrices
Description: Transition matrices (probabilities or counts) estimation for discrete Markov Chains of order n (1 <= n <= 5).

Title: Multivariate Cumulative Sum (MCUSUM) Control Chart
Description: mcusum package perform the Multivariate Cumulative Sum
(MCUSUM) Control Chart according to Crosier(1988)

Title: Does Monte Carlo hypothesis tests
Description:The package performs Monte Carlo hypothesis tests. It allows a couple of different sequential stopping boundaries (a truncated sequential probability ratio test boundary and a boundary proposed by Besag and Clifford, 1991). Gives valid p-values and confidence intervals on p-values.
Packaged: Wed Sep  6 14:23:08 2006; faym

Title: Monte Carlo hypothesis tests with Sequential Stopping
Description: The package performs Monte Carlo hypothesis tests. It
allows a couple of different sequential stopping boundaries (a
truncated sequential probability ratio test boundary and a
boundary proposed by Besag and Clifford, 1991). Gives valid
p-values and confidence intervals on p-values.