parametric statistics

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parametric statistics

statistics that assume that a population has a symmetric, such as a gaussian or normal, distribution.

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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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.
As conclusion regression model R5 is selected as the satisfactory model for parametric estimation of the urban railway system projects in Turkey.
The two ends of the estimation technique spectrum are parametric estimation and grassroots estimation.
The topics include designing and implementing network information systems for managing large construction projects, high-temperature failure mechanisms of multi-layer ceramic capacitors, designing health relaxation systems based on biofeedback from finger sensors, technical methods for international person authentication over a network, the self-organizing of network security systems based on non-optimum analysis, a novel method of reducing attributes for incomplete information systems, and parametric estimation for asymptotic regression models by a dynamical evolutionary algorithm.
The introductory chapter attempts to root the parametric estimation of macroeconomic systems in the general equilibrium theories of Walras and Pareto.
SEER for IT replicates real-world scenarios and outcomes by combining sophisticated cost modeling technology with an easy-to-use interface; databases of industry and user inputs, rates and factors; and a parametric estimation engine.
Founded in 1979, G A SEER Technologies is an industry-leading computer software and consulting company that develops and markets software based on parametric estimation technology.
G A SEER Technologies offers state-of-the-art software tools based on parametric estimation technology.
As is common in the literature (for example, Burnside and Dollar 2000; Clemens, Radelet, and Bhavnani 2004; Dalgaard, Hansen, and Tarp 2004; and Rajan and Subramanium 2005, to name a few), we use standard parametric estimations as benchmarks, although our conclusions are solely based on the semiparametric framework.

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