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Weighted.Desc.Stat  

Weighted Descriptive Statistics
View on CRAN: Click here


Download and install Weighted.Desc.Stat package within the R console
Install from CRAN:
install.packages("Weighted.Desc.Stat")

Install from Github:
library("remotes")
install_github("cran/Weighted.Desc.Stat")

Install by package version:
library("remotes")
install_version("Weighted.Desc.Stat", "1.0")



Attach the package and use:
library("Weighted.Desc.Stat")
Maintained by
Abbas Parchami
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-02-29
Latest Update: 2016-02-29
Description:
Weighted descriptive statistics is the discipline of quantitatively describing the main features of real-valued fuzzy data which usually given from a fuzzy population. One can summarize this special kind of fuzzy data numerically or graphically using this package. To interpret some of the properties of one or several sets of real-valued fuzzy data, numerically summarize is possible by some weighted statistics which are designed in this package such as mean, variance, covariance and correlation coefficent. Also, graphically interpretation can be given by weighted histogram and weighted scatter plot using this package to describe properties of real-valued fuzzy data set.
How to cite:
Abbas Parchami (2016). Weighted.Desc.Stat: Weighted Descriptive Statistics. R package version 1.0, https://cran.r-project.org/web/packages/Weighted.Desc.Stat
Previous versions and publish date:
No previous versions
Other packages that cited Weighted.Desc.Stat R package
View Weighted.Desc.Stat citation profile
Other R packages that Weighted.Desc.Stat depends, imports, suggests or enhances
Functions, R codes and Examples using the Weighted.Desc.Stat R package
Some associated functions: Weighted.Desc.Stat-package . w.ad . w.cov . w.cv . w.hist . w.kurtosis . w.mean . w.plot . w.r . w.sd . w.skewness . w.var . 
Some associated R codes: w.ad.R . w.cov.R . w.cv.R . w.hist.R . w.kurtosis.R . w.mean.R . w.plot.R . w.r.R . w.sd.R . w.skewness.R . w.var.R .  Full Weighted.Desc.Stat package functions and examples
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