learningRlab"

In LearningRlab: Statistical Learning Functions

library(LearningRlab)
library(graphics)
knitr::opts_chunk$set(
  comment = "#>", 
  collapse = TRUE
)

There are three families of fuctions in LearningRlab:

1. Main functions: these functions return the result of performing the process represented with the function.

2. Explained fuctions: these funcions returns the process itself to get the result, with the result.

3. User Interactive Functions: these functions maintain an interactive contact with the user to guide him in the resolution of the represented function.

Main Functions:

To explain the use of each function, we present a dataset to work with them:

data <- c(1,1,2,3,4,7,8,8,8,10,10,11,12,15,20,22,25)
plot(data); 
data2 <- c(1,1,4,5,5,5,7,8,10,10,10,11,20,22,22,24,25)
plot(data2);

#Binomial variables
n = 3
x = 2
p = 0.7

#Poisson variables
lam = 2
k = 3

#Normal variables
nor = 0.1

#T-Student variables
xt = 290 
ut = 310
st = 50
nt = 16

The arithmetic mean calculus function:

mean_(data)

The geometric mean calculus function:

geometricMean_(data)

The mode calculus function:

mode_(data)

The median calculus function:

median_(data)

The standard deviation calculus function:

standardDeviation_(data)

The average absolute deviation calculus function:

averageDeviation_(data)

The variance calculus function:

variance_(data)

The quartiles calculus function:

quartile_(data)

The percentile calculus function:

percentile_(data,0.3)

The absolute frecuency calculus function:

frecuency_abs(data,1)

The relative frecuency calculus function:

frecuency_relative(data,20)

The absolute acumulated frecuency calculus function:

frecuency_absolute_acum(data,1)

The relative acumulated frecuency calculus function:

frecuency_relative_acum(data,20)

The covariance calculus function:

covariance_(data, data2)

The harmonic mean calculus funtion:

harmonicMean_(data)

The pearson correlaction calculus funtion:

pearson_(data,data2)

The coefficient of variation calculus funtion:

cv_(data)

The Laplace rule calculus funtion:

laplace_(data,data2)

The binomial distribution calculus funtion:

binomial_(n,x,p)

The poisson distribution calculus funtion:

poisson_(k,lam)

The normal distribution calculus funtion:

normal_(nor)

The tstudent distribution calculus funtion:

tstudent_(xt,ut,st,nt)

The chisquared distribution calculus funtion:

chisquared_(data,data2)

The fisher distribution calculus funtion:

fisher_(data,data2)

Explained Functions:

For each main function, there are an explained function to see the calculus process:

• arithmetic mean:

explain.mean(data)

• geometric mean:

explain.geometricMean(data)

• mode:

explain.mode(data)

• median:

explain.median(data)

• standard deviation:

explain.standardDeviation(data)

• average absolute deviation:

explain.averageDeviation(data)

• variance:

explain.variance(data)

• quartile:

explain.quartile(data)

• percentile:

explain.percentile(data)

• absolute frecuency:

explain.absolute_frecuency(data,10)

• relative frecuency:

explain.relative_frecuency(data,8)

• absolute acumulated frecuency:

explain.absolute_acum_frecuency(data,10)

• relative acumulated frecuency:

explain.relative_acum_frecuency(data,8)

• covariance:

explain.covariance(data,data2)

• harmonic mean:

explain.harmonicMean(data)

• pearson correlaction:

explain.pearson(data,data2)

• coefficient of variation:

explain.cv(data)

• Laplace rule:

explain.laplace(data,data2)

• binomial distribution:

explain.binomial(n,x,p)

• poisson distribution:

explain.poisson(k,lam)

• normal distribution:

explain.normal(nor)

• tstudent distribution:

explain.tstudent(xt,ut,st,nt)

• chisquared distribution:

explain.chisquared(data,data2)

• fisher distribution:

explain.fisher(data,data2)

User Interactive Functions:

These functions are designed for the user to practice with them, and they are the following:

• interactive.mean()
• interactive.geometricMean()
• interactive.mode()
• interactive.median()
• interactive.standardDeviation()
• interactive.averageDeviation()
• interactive.variance()
• interactive.quartile()
• interactive.percentile()
• interactive.absolute_frecuency()
• interactive.relative_frecuency()
• interactive.absolute_acum_frecuency()
• interactive.relative_acum_frecuency()
• interactive.covariance()
• interactive.harmonicMean()
• interactive.pearson()
• interactive.cv()
• interactive.laplace()
• interactive.binomial()
• interactive.poisson()
• interactive.normal()
• interactive.tstudent()
• interactive.chisquared()
• interactive.fisher()

LearningRlab documentation built on Aug. 31, 2023, 1:08 a.m.