@stdlib/datasets-herndon-venus-semidiameters-cli
v0.2.2
Published
Fifteen observations of the vertical semidiameter of Venus, made by Lieutenant Herndon, with the meridian circle at Washington, in the year 1846.
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Venus Semidiameters
Fifteen observations of the vertical semidiameter of Venus, made by Lieutenant Herndon, with the meridian circle at Washington, in the year 1846.
Herndon's observations are a classic dataset commonly used in examples demonstrating outlier detection.
Installation
To use as a general utility, install the CLI package globally
npm install -g @stdlib/datasets-herndon-venus-semidiameters-cli
Usage
Usage: herndon-venus-semidiameters [options]
Options:
-h, --help Print this message.
-V, --version Print the package version.
Examples
$ herndon-venus-semidiameters
-0.30
-0.44
1.01
0.48
-0.24
0.06
0.63
-0.13
-1.40
-0.22
-0.05
0.20
0.18
0.39
0.10
References
- Chauvenet, William. 1868. A Manual of Spherical and Practical Astronomy. 5th ed. Vol. 5. London, England: Trübner & Co.
- Grubbs, Frank E. 1950. "Sample Criteria for Testing Outlying Observations." The Annals of Mathematical Statistics 21 (1). The Institute of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.
- Grubbs, Frank E. 1969. "Procedures for Detecting Outlying Observations in Samples." Technometrics 11 (1). Taylor & Francis: 1–21. doi:10.1080/00401706.1969.10490657.
- Tietjen, Gary L., and Roger H. Moore. 1972. "Some Grubbs-Type Statistics for the Detection of Several Outliers." Technometrics 14 (3). Taylor & Francis: 583–97. doi:10.1080/00401706.1972.10488948.
License
The data files (databases) are licensed under an Open Data Commons Public Domain Dedication & License 1.0 and their contents are licensed under Creative Commons Zero v1.0 Universal. The software is licensed under Apache License, Version 2.0.
See Also
@stdlib/datasets-herndon-venus-semidiameters
: fifteen observations of the vertical semidiameter of Venus, made by Lieutenant Herndon, with the meridian circle at Washington, in the year 1846.
Notice
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
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Copyright
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