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Books from the Library of Congress elementaryprinci00fish (User talk:Fæ/IA books#Fork5) (batch 1900-1924 #16571) File usage No pages on the English Wikipedia use this file (pages on other projects are not listed).
William Paul Cockshott (born 16 March 1952) is a Scottish academic in the fields of computer science and Marxist economics.He is a Reader at the University of Glasgow.Since 1993 he has authored multiple works in the tradition of scientific socialism, most notably Towards a New Socialism and How the World Works.
The book showed how operationally meaningful theorems can be described with a small number of analogous methods, thus providing "a general theory of economic theories." It moved mathematics out of the appendices (as in John R. Hicks's Value and Capital ) and helped change how standard economic analysis across subjects could be done with the ...
For example, economics researchers might hope to identify confounders, confidence intervals, and other parameters that are not well-specified in Machine Learning algorithms. [9] Machine learning may effectively enable the development of more complicated heterogeneous economic models. Traditionally, heterogeneous models required extensive ...
For example, in medical imaging, the boundaries of a tumor may be defined on an image or in a volume, for the purpose of measuring its size. The endocardial border may be defined on an image, perhaps during different phases of the cardiac cycle, for example, end-systole and end-diastole, for the purpose of assessing cardiac function.
Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist is a 2017 non-fiction book by Oxford economist Kate Raworth. [1] The book elaborates on her concept of doughnut economics , first developed in her 2012 paper, A Safe and Just Space for Humanity .
Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation of probability , as opposed to a relative-frequency interpretation.
Object-based image analysis has been applied in many fields, such as cell biology, medicine, earth sciences, and remote sensing. For example, it can detect changes of cellular shapes in the process of cell differentiation.; [6] it has also been widely used in the mapping community to generate land cover. [5] [7]