Imports: shiny, DT, shinydashboard, readxl

Title: Multivariate Outlier Detection and Imputation for Incomplete
person("Beat", "Hulliger", email = "beat.hulliger@fhnw.ch", role = "aut"),
person("Martin", "Sterchi", email = "martin.sterchi@fhnw.ch", role = "cre"))
Description: Algorithms for multivariate outlier detection when missing values occur.
Algorithms are based on Mahalanobis distance or data depth. Imputation is based
on the multivariate normal model or uses nearest neighbour donors. The algorithms
take sample designs, in particular weighting, into account. The methods are
described in Bill and Hulliger (2016) <doi:10.17713/ajs.v45i1.86>.
Imports: MASS (>= 7.3-50), norm (>= 1.0-9.5), stats, graphics, utils
Packaged: 2018-11-14 08:29:00 UTC; martin.sterchi

Title: Modified Mann Kendall Trend Tests with Variance Correction
Authors@R: person("Sandeep Kumar", "Patakamuri", email = "sandeep.patakamuri@gmail.com", role = c("aut", "cre"))
Description: Power of non-parametric Mann-Kendall test is highly influenced by serially correlated data. To address this issue, original time-series is modified by removing any trend component existing in the data and calculating effective sample size.
Hamed, K. H., & Ramachandra Rao, A. (1998). A modified Mann-Kendall trend test for auto correlated data. Journal of Hydrology, 204(1–4), 182–196. <doi:10.1016/S0022-1694(97)00125-X>.
Yue, S., & Wang, C. Y. (2004). The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series. Water Resources Management, 18(3), 201–218. <doi:10.1023/B:WARM.0000043140.61082.60>.
Author: Sandeep Kumar Patakamuri [aut, cre]
Maintainer: Sandeep Kumar Patakamuri <sandeep.patakamuri@gmail.com>

Title: Modified Mann Kendall Trend Tests
Description: Power of non-parametric Mann-Kendall test is highly influenced by serially correlated data. To address this issue, original time-series may be modified by the following approaches namely Prewhitening (PW), Trend Free Prewhitening (TFPW) and Modified Mann-Kendall tests through variance correction approaches, by calculating effective sample size.
Suggests: trend, testthat, knitr, rmarkdown, covr