Introduction to asrol
asrol calculates descriptive statistics in a user’s defined rolling-window or over a grouping variable. asrol can efficiently handle all types of data structures such as data declared as time series or panel data, undeclared data, or data with duplicate values, missing values, or data having time series gaps.
This version of asrol (version 5.0) significantly improves the calculation speed of the required statistics, thanks to the development of a more efficient algorithm for extracting rolling window indices. This has resulted in significant speed advantage for asrol compared to its previous versions or other available programs. The speed efficiency matters more in larger datasets. While writing the source code of asrol, I took the utmost care in making choices among available options. Therefore, every line of code had to undergo several tests to ensure accuracy and speed. In fact, there is a long list of built-in routines in asrol which are meant to handle different data structures. asrol intelligently identifies data structures and applies the most relevant routine from its library. Hence, asrol speed efficiency is ensured whether the data is rectangular (balanced panel), non-rectangular, has duplicates, has missing values, or has both duplicates and missing values.
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