A 'shiny' Module for Reading Excel Sheets
This is a shiny module that presents a file picker user interface to get an Excel file name, and reads the Excel sheets using 'readxl' package and returns the resulting sheet(s) as a vector and data in dataframe(s).

Multivariate Outlier Detection and Imputation for Incomplete
Survey Data
c(
person("Beat", "Hulliger", email = "beat.hulliger@fhnw.ch", role = "aut"),
person("Martin", "Sterchi", email = "martin.sterchi@fhnw.ch", role = "cre"))
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>.
MASS (>= 7.3-50), norm (>= 1.0-9.5), stats, graphics, utils
Beat Hulliger [aut],
Martin Sterchi [cre]

Modified Mann Kendall Trend Tests with Variance Correction
Approach
person("Sandeep Kumar", "Patakamuri", email = "sandeep.patakamuri@gmail.com", role = c("aut", "cre"))
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>.

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.
Yue, S., & Wang, C. Y. (2002) <doi:10.1029/2001WR000861>.
Yue, S., Pilon, P., Phinney, B., & Cavadias, G. (2002) <doi:10.1002/hyp.1095>.
Hamed, K. H., & Ramachandra Rao, A. (1998) <doi:10.1016/S0022-1694(97)00125-X>.
Yue, S., & Wang, C. Y. (2004) <doi:10.1023/B:WARM.0000043140.61082.60>.