Abakuks The Synoptic Problem and Statistics

1. Auflage 2014
ISBN: 978-1-4665-7202-7
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 215 Seiten

See How to Use Statistics for New Testament Interpretation

The Synoptic Problem and Statistics lays the foundations for a new area of interdisciplinary research that uses statistical techniques to investigate the synoptic problem in New Testament studies, which concerns the relationships between the Gospels of Matthew, Mark, and Luke. There are potential applications of the techniques to study other sets of similar documents.

Explore Hidden Markov Models for Textual Data

The book provides an introductory account of the synoptic problem and relevant theories, literature, and research at a level suitable for academic and professional statisticians. For those with no special interest in biblical studies or textual analysis, the book presents core statistical material on the use of hidden Markov models to analyze binary time series. Biblical scholars interested in the synoptic problem or in the use of statistical methods for textual analysis can omit the more technical/mathematical aspects of the book. The binary time series data sets and R code used are available on the author’s website.

Zielgruppe

Researchers in applied statistics; biblical scholars.

Autoren/Hrsg.

Abakuks, Andris

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Introduction to the gospel texts and the synoptic problem

The New Testament gospels

Manuscripts, critical editions and synopses

The synoptic problem and some proposed solutions

Statistics, verbal agreements, and sources of data
Outline of this book

The triple-link model

Introduction

The data

Probabilistic notation and assumptions

A probabilistic analysis

A statistical analysis

Double-link models

Matthew's and Luke's use of Mark: a logistic regression approach
Introduction
The data

Models for the univariate series

Models for the bivariate series

Hidden Markov models for binary time series

Introduction and motivation

Description of a hidden Markov model (HMM)

The likelihood function

Methods for computation
Choosing an HMM

Decoding

Matthew's and Luke's use of Mark: hidden Markov models

Introduction

Fitting hidden Markov models

Decoding the text of Mark for the fitted HMMs

Mark's and Luke's use of Matthew

Introduction

The data

Logistic regression

Hidden Markov models

Decoding

The minor agreements

Examples of synoptic parallels

Introduction

The Healing of a Leper

The Healing of the Paralytic

The Feeding of the Five Thousand

The Great Commandment

About David's Son

Jesus Mocked and Peter's Triple Denial

Comments on further pericopes

The Rich Young Man

The Healing of Bartimaeus

Final conclusions

Summary

Directions for future work

Appendix: R code for hidden Markov models

Bibliography

Author Index

Subject Index

Über Autor(innen)

Andris Abakuks is a lecturer in statistics at Birkbeck, University of London. His research focuses on the application of probability and statistics to problems in theology and New Testament studies.