parametric statistics

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parametric statistics

The class of statistics based on the assumption that the samples measured are from normally distributed populations.
See also: statistics
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The stability condition of the developed parametric estimation scheme is shown on the basis of the concepts of the small gain theorem.
Kamoun, "Parametric estimation of interconnected nonlinear systems described by input-output mathematical models," International Journal of Automation and Computing, vol.
In Figure 10 is shown the results of parametric estimation of the return value and its 95% CI for 14 years of hourly maxima.
Prediction performance of the linear regression model R5 and 2 neural network models were compared to determine a model with reasonable accuracy for parametric estimation of urban railway project costs.
The additive structure is present in many models of economic behavior, including the usual parametric estimation. Then given a data set, one could be interested in knowing what kind of structure follows the data.
If the Kristrom's method is compared with the linear parametric estimation the differences are not significant base on the overlapping of the confident intervals.
Distributions other than the gaussian can be used for parametric estimation of reference intervals; an analysis of the TSH data given in the Results assumes that the data are sampled from an exponential distribution.
They are the cornerstones of the parametric estimation technique developed by the RAND Corporation in the 1950s to predict the cost of aircraft.
Parametric estimation has made a great deal of progress since the days of ordinary least squares.
Hammerstein models are mentioned for example in applications to pH process control, where is used the poleplacement self-tuning control of nonlinear Hammerstein system [30], or in servo systems, where is employed the nonlinear modelling and predictive functional control of Hammerstein system [31], or like a recursive parametric estimation algorithm of multivariable systems described by Hammerstein models [26].
The ARC algorithm combines the parametric estimation of adaptive control with the robust stability of deterministic robust control.
Recently, [13] considered parametric estimation of the cumulative incidence function (CIF) for competing risks data subject to interval censoring.

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