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Visualizing Mortality Dynamics in the Lexis Diagram
Visualizing Mortality Dynamics in the Lexis Diagram
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The goal of this book is simple: We would like to show how mortality dynamics can be visualized in the so-called Lexis diagram. To appeal to as many potentialreaders as possible, we do not require any specialist knowledge. This approachmay be disappointing: Demographers may have liked more information aboutthe mathematical underpinnings of population dynamics on the Lexis surface asdemonstrated, for instance, by Arthur and Vaupel in 1984. Statisticians would haveprobably preferred more informat…

Visualizing Mortality Dynamics in the Lexis Diagram (el. knyga) (skaityta knyga) | knygos.lt

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The goal of this book is simple: We would like to show how mortality dynamics can be visualized in the so-called Lexis diagram. To appeal to as many potential

readers as possible, we do not require any specialist knowledge. This approach

may be disappointing: Demographers may have liked more information about

the mathematical underpinnings of population dynamics on the Lexis surface as

demonstrated, for instance, by Arthur and Vaupel in 1984. Statisticians would have

probably preferred more information about the underlying smoothing methods that

were used. Epidemiologists likewise might miss discussions about the etiology of

diseases. Sociologists would have probably expected that our results were more

embedded into theoretical frameworks...

This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
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The goal of this book is simple: We would like to show how mortality dynamics can be visualized in the so-called Lexis diagram. To appeal to as many potential

readers as possible, we do not require any specialist knowledge. This approach

may be disappointing: Demographers may have liked more information about

the mathematical underpinnings of population dynamics on the Lexis surface as

demonstrated, for instance, by Arthur and Vaupel in 1984. Statisticians would have

probably preferred more information about the underlying smoothing methods that

were used. Epidemiologists likewise might miss discussions about the etiology of

diseases. Sociologists would have probably expected that our results were more

embedded into theoretical frameworks...

This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

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