Abstract
A local version of the central limit theorem is established for normalized sums of dependent random variables when a global theorem is known and conditional distributions are sufficiently smooth. The proof uses ideas from Statistics, by representing the density as the integral of a score function for a translation family of distributions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.