Estimation of the Life Expectancy of Tenants in the Middle Ages
In: Mathematical population studies: an international journal of mathematical demography, Band 16, Heft 2, S. 131-152
ISSN: 1547-724X
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In: Mathematical population studies: an international journal of mathematical demography, Band 16, Heft 2, S. 131-152
ISSN: 1547-724X
In: The economic history review, Band 58, Heft 2, S. 272-309
ISSN: 1468-0289
New micro‐level data have recently become available for three provinces of The Netherlands for the period 1812–1912, which allow the study of the evolution of socio‐economic differentials in infant and childhood mortality. The authors found significant differences in the levels of infant mortality by social group between the three provinces, and a wide variety in the pattern of social inequality. This showed the importance of the regional environment for the level of infant mortality in the nineteenth century. Contrary to expectations, strong social differences were also observed in neonatal mortality. Being born in an urban environment did not have a strong effect on survival during the first year of birth.
In: Proces: tijdschrift voor strafrechtspleging, Band 96, Heft 6, S. 398-406
Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models. In An Introduction to Mathematical Statistics the authors describe key concepts from statistics and give a mathematical basis for important statistical methods. Much attention is paid to the sound application of those methods to data. The three main topics in statistics are estimators, tests, and confidence regions. The authors illustrate these in many examples, with a separate chapter on regression models, including linear regression and analysis of variance. They also discuss the optimality of estimators and tests, as well as the selection of the best-fitting model. Each chapter ends with a case study in which the described statistical methods are applied. This book assumes a basic knowledge of probability theory, calculus, and linear algebra.--
In: Statistica Neerlandica: journal of the Netherlands Society for Statistics and Operations Research, Band 65, Heft 3, S. 239-258
ISSN: 1467-9574
We consider estimation and testing of linkage equilibrium from genotypic data on a random sample of sibs, such as monozygotic and dizygotic twins. We compute the maximum likelihood estimator with an EM‐algorithm and a likelihood ratio statistic that takes the family structure into account. As we are interested in applying this to twin data we also allow observations on single children, so that monozygotic twins can be included. We allow non‐zero recombination fraction between the loci of interest, so that linkage disequilibrium between both linked and unlinked loci can be tested. The EM‐algorithm for computing the maximum likelihood estimator of the haplotype frequencies and the likelihood ratio test‐statistic, are described in detail. It is shown that the usual estimators of haplotype frequencies based on ignoring that the sibs are related are inefficient, and the likelihood ratio test for testing that the loci are in linkage disequilibrium.