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A modeling paradigm incorporating parametric and non-parametric methods
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2005A novel parametric/non-parametric modeling paradigm was defined and used in characterization of synaptic transmission. In this paradigm, parametric and nonparametric techniques were incorporated in a complementary manner. Non-parametric method was used to generalize experimental data and extract system input/output properties.
D, Song +3 more
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Non-parametric Statistical Methods
1987Basic statistics and econometrics courses stress methods based on assuming that the data or error term in regression models follow the normal distribution. Indeed, the efficiency of least squares estimates relies on the assumption of normality. In order to lessen the dependence of statistical inference on that assumption statisticians developed methods
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Non-Parametric Analysis Methods
2001As mentioned in Chapter 6, non-parametric tests are applicable in two circumstances: (1) when parametric tests cannot be used owing to the scale of the response variable, that is, the scale is nominal or ordinal, and (2) when, even when the scale of the response variable admits the use of parametric tests, that is, it is an interval or ratio scale, the
Natalia Juristo, Ana M. Moreno
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Parametric and Non-Parametric Regression Methods
2023T. Agami Reddy, Gregor P. Henze
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A comparison of parametric and non-parametric methods for runoff forecasting
Hydrological Sciences Journal, 1990Abstract The paper evaluates the performance of a non-parametric scheme, the nearest neighbour (NN) method, to predict the daily mean discharge in a mountain basin supplying a hydroelectric reservoir in northeastern Italy. The results are compared with those of an autoregressive model with exogenous input (ARX), coupled with a previously developed snow
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Non-parametric and robust methods
1992The history of the statistical analysis of quantal response data is documented by Finney (1971, pp 38–42). The maximum-likelihood fitting of the probit model stems from the papers of Fisher (1935) and Bliss (1938). However, non-parametric approaches to estimating the ED 50 have a generally earlier origin, in papers such as Behrens (1929), Karber (1931)
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Non-Parametric Spectral Methods
2015This chapter deals with obtaining a good estimate of the power spectrum of a random signal on the basis of a finite number of samples of a typical realization of the underlying random process—one among the infinite sequences that the process can generate when we measure it.
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A non-parametric confidence interval method
European Journal of Clinical Pharmacology, 1985A. Racine-Poon +3 more
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