Original title: The scalar-valued score functions of continuous probability distribution
Authors: Fabián, Zdeněk
Document type: Research reports
Year: 2019
Language: eng
Series: Technical Report, volume: V-1264
Abstract: In this report we give theoretical basis of probability theory of continuous random variables based on scalar valued score functions. We maintain consistently the following point of view: It is not the observed value, which is to be used in probabilistic and statistical considerations, but its 'treated form', the value of the scalar-valued score function of distribution of the assumed model. Actually, the opinion that an observed value of random variable should be 'treated' with respect to underlying model is one of main ideas of the inference based on likelihood in classical statistics. However, a vector nature of Fisher score functions of classical statistics does not enable a consistent use of this point of view. Instead, various inference functions are suggested and used in solutions of various statistical problems. Inference function of this report is the scalar-valued score function of distribution.
Keywords: Characteristics of continous random variables; Parametric estimation; Scalar-valued score functions; Shortcomings of probability theory; Skew-symmetric distributions; Transformed distributions

Institution: Institute of Computer Science AS ČR (web)
Document availability information: Fulltext is available at the institute of the Academy of Sciences.
Original record: http://hdl.handle.net/11104/0295464

Permalink: http://www.nusl.cz/ntk/nusl-393863


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Research > Institutes ASCR > Institute of Computer Science
Reports > Research reports
 Record created 2019-03-28, last modified 2020-03-27


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