Idea
In the @stdlib/stats namespace, we implement a number of hypothesis tests (e.g., z-test, t-test, chi-square test, Bartlett test, and more). Recently, we began work to create lower-level strided array implementations (e.g., see @stdlib/stats/strided/dztest). These strided APIs allow us to create type-specialized implementations which can be implemented in both JavaScript and C, and they allow us to create higher-level ndarray APIs which can operate on one or more ndarray dimensions.
The goal of this idea is to build on the work implementing strided APIs for ztest and ztest2 to implement strided APIs for the remainder of the statistical hypothesis test APIs.
For those interested in this idea, you should
Expected Outcomes
Users will be able to use strided implemented APIs to operate on one-dimensional strided arrays.
Involved Software
No other software is necessary.
Prerequisite Knowledge
JavaScript, Node.js.
Difficulty
Intermediate. There may be some instances where we will need to ensure implementation of certain functions in C (e.g., certain stats/base/dists/* packages) and those may vary in difficulty (e.g., beta functions).
Project Length
90/175/350 hours. Can be scoped accordingly. Scope can be expanded to implement additional statistical hypothesis tests which are not currently available in stdlib.
Idea
In the
@stdlib/statsnamespace, we implement a number of hypothesis tests (e.g., z-test, t-test, chi-square test, Bartlett test, and more). Recently, we began work to create lower-level strided array implementations (e.g., see@stdlib/stats/strided/dztest). These strided APIs allow us to create type-specialized implementations which can be implemented in both JavaScript and C, and they allow us to create higher-level ndarray APIs which can operate on one or more ndarray dimensions.The goal of this idea is to build on the work implementing strided APIs for
ztestandztest2to implement strided APIs for the remainder of the statistical hypothesis test APIs.For those interested in this idea, you should
Expected Outcomes
Users will be able to use strided implemented APIs to operate on one-dimensional strided arrays.
Involved Software
No other software is necessary.
Prerequisite Knowledge
JavaScript, Node.js.
Difficulty
Intermediate. There may be some instances where we will need to ensure implementation of certain functions in C (e.g., certain
stats/base/dists/*packages) and those may vary in difficulty (e.g., beta functions).Project Length
90/175/350 hours. Can be scoped accordingly. Scope can be expanded to implement additional statistical hypothesis tests which are not currently available in stdlib.