knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-")
"R CMD build --no-build-vignettes pkgname" 

resumeRdesc

The goal of resumeRdesc is to get a entire summary statistic.

You have installed resumeRdesc on your R system, version 3.4.4 or later “https://cran.r-project.org/”. Works better in Rstudio “https://www.rstudio.com”

Installation

You can install the released version of resumeRdesc from CRAN with:

install.packages("resumeRdesc"). Not yet available

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("osoramirez/resumeRdesc")

Example

Activate the resumeRdesc package:

library(resumeRdesc)

You could requiere “e1071”; “car” and “carData” package

This is a basic example which shows you how to solve a common problem:

set.seed(12345)
data<-rnorm(100)
resume(rnorm(100))

Get a complete summary table, histogram and boxplot of your distribution data.

resume2data(data)

If you are interested in exploring the distribution of your data using a histogram, use “plothist”.

plothist(data)

You can also embed boxplot, for example:

plotbox(data)

Coefficient of variation

A coefficient of variation (cv) is a statistical measure of the dispersion of data points in a data series around the mean.

cv(data)

Geometric mean

The geometric mean is a mean or average, which indicates the central tendency

g_mean(data)

Harmonic mean

The harmonic mean is a very specific type of average. It’s generally used when dealing with averages of units, like speed or other rates and ratios. Its a reciprocals of the numbers in your data set or it is calculated by dividing the number of observations by the reciprocal of each number in the series.

h_mean(data)

Mode

The "Mode" is the value that occurs most often. If no number in the list is repeated.

data2<-c(1,1,1,2,3,4,5,6,7,8,9)
Mode(data2)

Standard error

Is as a measure of the precision of the sample mean, it is considered as a measures of spread.

se(data)

Kurtosis

Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution.

K(data)

Skewness

Skewness is a measure of symmetry, or the lack of symmetry.

skew(data)

summaries for data.frame

For your data.frame data use this functions.

data(iris)
resumendf(Petal.Width ~Species, data = iris)

Reference

Read more: Harmonic Mean https://www.investopedia.com/terms/h/harmonicaverage.asp#ixzz5Ibmy4Rbq

Read more: Coefficient Of Variation (CV) https://www.investopedia.com/terms/c/coefficientofvariation.asp#ixzz5Ibl3v4Ly

Read more: Standard error https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1255808/



osoramirez/resumeRdesc documentation built on May 31, 2019, 5:13 p.m.