cigarettes

A dataset containing life expectancy and cigarettes per day.

datasets

The computational complexity of the implemented algorithm for
Kendall's correlation is O(n log(n)), which is faster than the base R
implementation with a computational complexity of O(n^2). For small vectors
(i.e., less than 100 observations), the time difference is negligible.
However, for larger vectors, the speed difference can be substantial and the
numerical difference is minimal. The references are
Knight (1966) <doi:10.2307/2282833>,
Abrevaya (1999) <doi:10.1016/S0165-1765(98)00255-9>,
Christensen (2005) <doi:10.1007/BF02736122> and
Emara (2024) <https://learningcpp.org/>.
This implementation is described in
Vargas Sepulveda (2024) <doi:10.48550/arXiv.2408.09618>.

Mauricio Vargas

kendallknight

Efficient Implementation of Kendall's Correlation Coefficient
Computation

Mauricio Vargas Sepulveda

Loader Catherine

Ross Ihaka

cigarettes function

A data frame with 15 rows and 2 variables:<dl>
<dt>life_expectancy</dt>
<dd>Life expectancy in years.</dd><dt>cigarettes_per_day</dt>
<dd>Cigarettes smoked per day.</dd>
</dl>

Format

Life expectancy and cigarettes per day — cigarettes

A data frame with 15 rows and 2 variables:<dl>
<dt>life_expectancy</dt>
<dd>Life expectancy in years.</dd>

<dt>cigarettes_per_day</dt>
<dd>Cigarettes smoked per day.</dd>


</dl>

cigarettes: Life expectancy and cigarettes per day

Description

Usage

Arguments

Format

Examples