The Jackknife: A cost-efficient alternative to bootstrap variance estimation
Date of Publication
2008
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Statistics Major in Actuarial Science
Subject Categories
Physical Sciences and Mathematics
College
College of Science
Department/Unit
Mathematics and Statistics
Thesis Adviser
Arturo Pacificador
Defense Panel Chair
Regina M. Tresvalles
Defense Panel Member
Rechel G. Arcilla
Michele G. Tan
Abstract/Summary
This thesis presents the Jackknife Variance Estimator as a cost efficient alternative to the Bootstrap Variance Estimator. The Jackknife and the Bootstrap are both Resampling methodologies. This mean that they can provide a variance estimate to estimation problems, even when complexities in the sampling design and the estimator form would make it difficult or impossible for conventional method to do so.
The researcher provided the compilation of properties and a select history of the Jackknife, from numerous sources. Also, the researcher provided a comparison between the Jackknife Variance and the Bootstrap Variance estimator, under a simple random experiment in the estimation of the sample median.
Abstract Format
html
Language
English
Format
Accession Number
TU15429
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
vii, 41 leaves ; ill. (some col.) ; 28 cm.
Keywords
Estimation theory; Jackknife (Statistics); Bootstrap (Statistics); Resampling (Statistics)
Recommended Citation
Obligacion, G. P. (2008). The Jackknife: A cost-efficient alternative to bootstrap variance estimation. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/2308
