Statistical inference based on the nonparametric maximum likelihood estimator under double-truncation
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| 001 | 605476098 | ||
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| 008 | 210128e20150701xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s10985-014-9297-5 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s10985-014-9297-5 | ||
| 245 | 0 | 0 | |a Statistical inference based on the nonparametric maximum likelihood estimator under double-truncation |h [Elektronische Daten] |c [Takeshi Emura, Yoshihiko Konno, Hirofumi Michimae] |
| 520 | 3 | |a Doubly truncated data consist of samples whose observed values fall between the right- and left- truncation limits. With such samples, the distribution function of interest is estimated using the nonparametric maximum likelihood estimator (NPMLE) that is obtained through a self-consistency algorithm. Owing to the complicated asymptotic distribution of the NPMLE, the bootstrap method has been suggested for statistical inference. This paper proposes a closed-form estimator for the asymptotic covariance function of the NPMLE, which is computationally attractive alternative to bootstrapping. Furthermore, we develop various statistical inference procedures, such as confidence interval, goodness-of-fit tests, and confidence bands to demonstrate the usefulness of the proposed covariance estimator. Simulations are performed to compare the proposed method with both the bootstrap and jackknife methods. The methods are illustrated using the childhood cancer dataset. | |
| 540 | |a Springer Science+Business Media New York, 2014 | ||
| 690 | 7 | |a Asymptotic variance |2 nationallicence | |
| 690 | 7 | |a Bootstrap |2 nationallicence | |
| 690 | 7 | |a Confidence band |2 nationallicence | |
| 690 | 7 | |a Goodness-of-fit test |2 nationallicence | |
| 690 | 7 | |a Survival analysis |2 nationallicence | |
| 700 | 1 | |a Emura |D Takeshi |u Graduate Institute of Statistics, National Central University, Zhongli, Taiwan |4 aut | |
| 700 | 1 | |a Konno |D Yoshihiko |u Department of Mathematical and Physical Sciences, Japan Women's University, Tokyo, Japan |4 aut | |
| 700 | 1 | |a Michimae |D Hirofumi |u Department of Clinical Medicine (Biostatistics), School of Pharmacy, Kitasato University, Tokyo, Japan |4 aut | |
| 773 | 0 | |t Lifetime Data Analysis |d Springer US; http://www.springer-ny.com |g 21/3(2015-07-01), 397-418 |x 1380-7870 |q 21:3<397 |1 2015 |2 21 |o 10985 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s10985-014-9297-5 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s10985-014-9297-5 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Emura |D Takeshi |u Graduate Institute of Statistics, National Central University, Zhongli, Taiwan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Konno |D Yoshihiko |u Department of Mathematical and Physical Sciences, Japan Women's University, Tokyo, Japan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Michimae |D Hirofumi |u Department of Clinical Medicine (Biostatistics), School of Pharmacy, Kitasato University, Tokyo, Japan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Lifetime Data Analysis |d Springer US; http://www.springer-ny.com |g 21/3(2015-07-01), 397-418 |x 1380-7870 |q 21:3<397 |1 2015 |2 21 |o 10985 | ||