The DOI matches its Crossref record.
Approximations for Digital Computers
Abstract
Numerical analysts and computer operators in all fields will welcome this publication in book form of Cecil Hastings' well-known approximations for digital computers, formerly issued in loose sheets and available only to a limited number of specialists. In a new method that combines judgment and intuition with mathematics, Mr. Hasting has evolved a set of approximations which far surpasses in simplicity earlier approximations developed by conventional methods. Part I of this book introduces the collection of useful and illustrative approximations, each of which is presented with a carefully drawn error curve in Part II. Originally published in 1955. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
Xiu, D., & Karniadakis, G. E. (2002) · SIAM Journal on Scientific Computing · doi:10.1137/s1064827501387826 · Cited by 4,807
Optimal nonuniform signaling for Gaussian channels
Kschischang, F. R., & Pasupathy, S. (1993) · IEEE Transactions on Information Theory · doi:10.1109/18.256499 · Cited by 503
Bootstrapping the Gini Coefficient of Inequality
Dixon, P. M., Weiner, J., Mitchell-Olds, T., & Woodley, R. (1987) · Ecology · doi:10.2307/1939238 · Cited by 305
Oexle, K. (2010) · Journal of Human Genetics · doi:10.1038/jhg.2010.9 · Cited by 8
Metadata
- Authors
- Hastings, C., Wayward, J. T., & Wong, J. P.
- Venue
- Princeton University Press eBooks
- Publisher
- Princeton University Press
- Published
- 1955-12-31
- OpenAlex
- W2167274974
- Cited by
- 830
- References
- 0
- FWCI
- 16.63
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Approximations for Digital Computers. https://app.cochat.ai/papers/10.1515/9781400875597
- The paper
- Hastings, C., Wayward, J. T., & Wong, J. P. (1955). Approximations for Digital Computers. Princeton University Press eBooks. https://doi.org/10.1515/9781400875597
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
