Overview

distrr provides some tools to estimate and manage empirical distributions. In particular, one of the main features of distrr is the creation of data cubes of estimated statistics, that include all the combinations of the variables of interest. The package makes strong usage of the tools provided by dplyr, which is a grammar of data manipulation.

The main functions to create a data cube are dcc5() and dcc6() (dcc stands for data cube creation).

The data cube creation is like:

data %>%
  group_by(some variables) %>%
  summarise(one or more estimated statistic)

in dplyr terms, but the operation is done for each possible combination of the variables used for grouping. The result will be a data frame in “tidy form”. See some examples in the Usage section below.

Installation

# From CRAN
install.packages("distrr")


# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("gibonet/distrr")

Usage

Consider the invented_wages dataset:

If we want to count the number of observations and estimate the average wage by gender, with dplyr we can do:

We can estimate the same statistics but grouped by education by changing the argument inside group_by:

and estimate the statistics by gender and education including both variables in group_by:

With dcc5 we can perform all the steps above with one call:

The resulting data frame contains a column for each grouping variable, and the estimations of all the combinations of the variables:

  • by gender
  • by education
  • by gender and education
  • plus the same statistics for all the dataset, without any grouping (this can be set with the argument .all, which by default is TRUE).

Note that in the result there are some rows where the variables take the value "Totale". When a variable has this value, it means that the subset of the data considered in that row contains all the values of the variable. For example, the first row of the result of dcc5 contains the estimations for all the dataset. The value "Totale" can be changed with the argument .total.

The same result of dcc5 can be produced by dcc6, with a slightly different approach.

Compared to the results obtained with dcc5, we added the weighted average of wages and changed the "Totale" value to "TOTAL".