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- Twisting_properties abstract "Starting with a sample observed from a random variable X having a given distribution law with a non-set parameter, a parametric inference problem consists of computing suitable values – call them estimates – of this parameter precisely on the basis of the sample. An estimate is suitable if replacing it with the unknown parameter does not cause major damage in next computations. In algorithmic inference, suitability of an estimate reads in terms of compatibility with the observed sample. In turn, parameter compatibility is a probability measure that we derive from the probability distribution of the random variable to which the parameter refers. In this way we identify a random parameter Θ compatible with an observed sample.Given a sampling mechanism , the rationale of this operation lies in using the Z seed distribution law to determine both the X distribution law for the given θ, and the Θ distribution law given an X sample. Hence, we may derive the latter distribution directly from the former if we are able to relate domains of the sample space to subsets of Θ support. In more abstract terms, we speak about twisting properties of samples with properties of parameters and identify the former with statistics that are suitable for this exchange, so denoting a well behavior w.r.t. the unknown parameters. The operational goal is to write the analytic expression of the cumulative distribution function , in light of the observed value s of a statistic S, as a function of the S distribution law when the X parameter is exactly θ.".
- Twisting_properties wikiPageID "20890522".
- Twisting_properties wikiPageRevisionID "526589531".
- Twisting_properties hasPhotoCollection Twisting_properties.
- Twisting_properties subject Category:Algorithmic_inference.
- Twisting_properties subject Category:Computational_statistics.
- Twisting_properties type Abstraction100002137.
- Twisting_properties type Act100030358.
- Twisting_properties type Activity100407535.
- Twisting_properties type Algorithm105847438.
- Twisting_properties type Event100029378.
- Twisting_properties type Procedure101023820.
- Twisting_properties type PsychologicalFeature100023100.
- Twisting_properties type Rule105846932.
- Twisting_properties type StatisticalAlgorithms.
- Twisting_properties type YagoPermanentlyLocatedEntity.
- Twisting_properties comment "Starting with a sample observed from a random variable X having a given distribution law with a non-set parameter, a parametric inference problem consists of computing suitable values – call them estimates – of this parameter precisely on the basis of the sample. An estimate is suitable if replacing it with the unknown parameter does not cause major damage in next computations. In algorithmic inference, suitability of an estimate reads in terms of compatibility with the observed sample.".
- Twisting_properties label "Twisting properties".
- Twisting_properties sameAs m.05b37y3.
- Twisting_properties sameAs Q7858585.
- Twisting_properties sameAs Q7858585.
- Twisting_properties sameAs Twisting_properties.
- Twisting_properties wasDerivedFrom Twisting_properties?oldid=526589531.
- Twisting_properties isPrimaryTopicOf Twisting_properties.