Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 506

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Smoothing Counting Process Intensities by Means of Kernel Functions

Open access
Ramlau-Hansen, Henrik·1983·The Annals of Statistics
DOI 10.1214/aos/1176346152
Open this paper in CoChat — free account

Abstract

The kernel function method developed during the last twenty-five years to estimate a probability density function essentially is a way of smoothing the empirical distribution function. This paper shows how one can generalize this method to estimate counting process intensities using kernel functions to smooth the nonparametric Nelson estimator for the cumulative intensity. The properties of the estimator for the intensity itself are investigated, and uniform consistency and asymptotic normality are proved. We also give an illustrative numerical example.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1214/aos/1176346152

Cites

9 of 9 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 9 references

Cited by

See all 506

Metadata

Authors
Ramlau-Hansen, H.
Venue
The Annals of Statistics
Publisher
Institute of Mathematical Statistics
Published
1983-06-01
Volume
11
Issue
2
ISSN
0090-5364 (ISSN-L)
DOI
10.1214/aos/1176346152
OpenAlex
W2071216735
Cited by
506
References
9
FWCI
9.74
Type
journal article
Language
en
Open access
bronze

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: Smoothing Counting Process Intensities by Means of Kernel Functions. https://app.cochat.ai/papers/10.1214/aos/1176346152
The paper
Ramlau-Hansen, H. (1983). Smoothing Counting Process Intensities by Means of Kernel Functions. The Annals of Statistics. https://doi.org/10.1214/aos/1176346152

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.