The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
On the Kolmogorov-Smirnov Test for the Exponential Distribution with Mean Unknown
Abstract
The standard tables used for the Kolmogorov-Smirnov test are valid when testing whether a set of observations are from a completely specified continuous distribution. If one or more parameters must be estimated from the sample then the tables are no longer valid. A table is given in this note for use with the Kolmogorov-Smirnov statistic for testing whether a set of observations is from an exponential population when the mean is not specified but must be estimated from the sample. The table is obtained from a Monte Carlo calculation.
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
Cites
The Kolmogorov-Smirnov Test for Goodness of Fit
Massey, F. J. (1951) · Journal of the American Statistical Association · doi:10.1080/01621459.1951.10500769 · Cited by 7,210
Cited by
EDF Statistics for Goodness of Fit and Some Comparisons
Stephens, M. A. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10480196 · Cited by 3,166
Comparisons of various types of normality tests
Yap, B. W., & Sim, C. H. (2011) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2010.520163 · Cited by 897
Problems with fitting to the power-law distribution
Goldstein, M. L., Morris, S. A., & Yen, G. G. (2004) · The European Physical Journal B · doi:10.1140/epjb/e2004-00316-5 · Cited by 495
Improved goodness-of-fit tests
FINKELSTEIN, J. M., & SCHAFER, R. E. (1971) · Biometrika · doi:10.1093/biomet/58.3.641 · Cited by 340
Aronov, D., Veit, L., Goldberg, J. H., & Fee, M. S. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.3009-11.2011 · Cited by 64
“The goodness-of-fit of the exponential was estimated using the Lilliefors statistic (Lilliefors, 1969), a procedure similar to the Kolmogorov–Smirnov test but suitable for evaluating fits.”
Method
Metadata
- Authors
- Lilliefors, H. W.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1969-03
- Volume
- 64
- Issue
- 325
- Pages
- 387-389
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2039486340
- Cited by
- 637
- References
- 1
- FWCI
- 4.80
- Type
- journal article
- 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: On the Kolmogorov-Smirnov Test for the Exponential Distribution with Mean Unknown. https://app.cochat.ai/papers/10.1080/01621459.1969.10500983
- The paper
- Lilliefors, H. W. (1969). On the Kolmogorov-Smirnov Test for the Exponential Distribution with Mean Unknown. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1969.10500983
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.
