Journals / Technological Applied Sciences / 2019 / Cilt: 14 Sayı: 4

An R Package for Multivariate Hypothesis Tests: MVTests

Hasan Bulut(ONDOKUZ MAYIS UNIVERSITY)0000-0002-6924-9651
Pages
132–138
Publication Date
2019-10-26
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Therefore, it is believed that this study is a helpful tool for researchers and users.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent years, the R program is widely used for statistical analysis.
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Key Findings & Data:Because the R program is open source software, it may contain the R packages developed by users.
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Conclusion & Impact:Therefore, it is believed that this study is a helpful tool for researchers and users.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:MVTests · Box-M · MANOVA

Özet

In recent years, the R program is widely used for statistical analysis. Because the R program is open source software, it may contain the R packages developed by users. This study aims to promote an R package entitled MVTests, which consists of multivariate hypothesis tests. By using this package, one performs hypothesis tests, which are used widely and related to each other, such as One-Way MANOVA, multivariate normality tests, Box-M test. In this study, the theoretical background of these tests and their applications with MVTests package are given. Users test easily to their data with MVTests package. Therefore, it is believed that this study is a helpful tool for researchers and users.

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Cite This Article

Bulut, H. (2019). An R Package for Multivariate Hypothesis Tests: MVTests. Technological Applied Sciences, Cilt: 14 Sayı: 4, 132–138. https://ajindex.com/articles/1007655

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References (10)

  1. Bulut, H., (2018). MVTests: Multivariate Hypothesis Tests. R package version 1.1. URL: https://cran.r-project.org/web/packages/MVTests/MVTests.pdf.
  2. Shapiro, S.S. and Wilk, M.B., (1965). An Analysis of Variance Test for Normality (complete samples). Biometrika, 52(3/4):591-611.
  3. Villasenor Alva, J.A. and Estrada, E.G., (2009). A Generalization of Shapiro–Wilk's Test for Multivariate Normality. Communications in Statistics—Theory and Methods, 38(11):1870-1883.
  4. Rencher, A.C., (2003). Methods of Multivariate Analysis (Vol. 492). John Wiley & Sons.
  5. Bulut, H., (2018). R Uygulamaları ile Çok Değişkenli İstatistiksel Yöntemler. Nobel Akademik Yayıncılık, Ankara, Türkiye.
  6. Tatlidil, H., (1996). Uygulamalı Çok Değişkenli İstatistiksel Yöntemler. Cem Web., Ankara, Türkiye.
  7. Nel, D.G. and Van der Merwe, C.A., (1986). A Solution to the Multivariate Behrens-Fisher Problem. Communications in Statistics-Theory and Methods, 15(12):3719-3735.
  8. https://cran.r-project.org/.
  9. James, G.S., (1954). Tests of Linear Hypotheses in Univariate and Multivariate Analysis When the Ratios of the Population Variances are Unknown. Biometrika, 41(1/2):19-43.
  10. Tsagris, M.T., (2014). Multivariate Statistical Functions in R. Athens, Nottingham and Abu Halifa (Kuwait).