Information bounds and nonparametric maximum likelihood estimation
P. Groeneboom
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Information bounds and nonparametric maximum likelihood estimation
Published
Jul 31, 1992
Publisher
Springer My Copy UK
Pages
136
ISBN-13
9783034886222
ISBN-10
3034886225
Description
The book gives an account of recent developments in the theory of nonparametric and semiparametric estimation. The first part deals with information lower bounds and differentiable functionals. The second part focuses on nonparametric maximum likelihood estimators for interval censoring and deconvolution. The distribution theory of these estimators is developed and new algorithms for computing them are introduced. The models apply frequently in biostatistics and epidemiology and although they have been used as a data-analytic tool for a long time, their properties have been largely unknown. Contents: Part I. Information Bounds: 1. Models, scores, and tangent spaces • 2. Convolution and asymptotic minimax theorems • 3. Van der Vaart's Differentiability Theorem • PART II. Nonparametric Maximum Likelihood Estimation: 1. The interval censoring problem • 2. The deconvolution problem • 3. Algorithms • 4. Consistency • 5. Distribution theory • References
Sisters of the Yam
Modern Spectral Estimation
Detection, estimation, and modulation theory
Decision and estimation theory
Les objets fractals
Handbook of nonlinear regression models
Frequently Asked Questions
How many pages are in Information bounds and nonparametric maximum likelihood estimation?
This edition of Information bounds and nonparametric maximum likelihood estimation has approximately 136 pages. Please note, this is an estimate and the exact page count can vary between hardcover, paperback, and e-book versions.
How long does it take to read Information bounds and nonparametric maximum likelihood estimation?
For most readers, Information bounds and nonparametric maximum likelihood estimation typically takes between 2h 50m and 1h 53m to complete. This is based on the book's length of approximately 34,000 words and common reading speeds.
Here's a detailed breakdown: • Continuous reading at 250 WPM: approximately 2h 16m of focused reading • Casual reading (30 minutes/day): you could finish in roughly 5 days • Estimated word count: 34,000 words
Your individual reading time will vary based on your personal reading pace, the amount of daily reading time, and your familiarity with the subject matter.
What is the word count of Information bounds and nonparametric maximum likelihood estimation?
The estimated word count for Information bounds and nonparametric maximum likelihood estimation is approximately 34,000 words. This figure is calculated using industry-standard methods that consider genre-specific word density patterns, typical formatting and layout characteristics, and standard words-per-page ratios for published books.
This is an approximation — actual word count may vary based on font size, formatting, edition, and the presence of illustrations or charts.
Who is the author of Information bounds and nonparametric maximum likelihood estimation?
Information bounds and nonparametric maximum likelihood estimation was written by P. Groeneboom.
When was Information bounds and nonparametric maximum likelihood estimation published?
The publication date for this specific edition is Jul 31, 1992. The original work may have been published on a different date.