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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 Methods for Linear Extraction
2004This article presents two new approaches, one parametric and one non-parametric, to the linear grouping of image features. They are based on the Bayesian Hough Transform, which takes into account feature uncertainty. Our main contribution are two new ways to detect the most significant modes of the Hough Transform.
Benedicte Bascle +2 more
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Non‐Linearities in Electricity Demand and Temperature: Parametric Versus Non‐Parametric Methods
Oxford Bulletin of Economics and Statistics, 1997This paper investigates the relationship between outside air temperature and the residential demand for space heating energy. These non‐linearities are investigated empirically using high frequency panel data for a sample of UK households, and both parametric and non‐parametric methods for identifying non‐linearities are examined.
Andrew Henley, John Peirson
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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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Parametric and Non-Parametric Regression Methods
2023T. Agami Reddy, Gregor P. Henze
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Non-Parametric Statistic Methods
In this chapter, we will explore various methods and statistical tests used in hypothesis validation and sample comparison. We will begin with an introduction to the formulation of scientific and statistical hypotheses and discuss the determination of the appropriate sample size.openaire +1 more source
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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Portfolio construction using parametric and non-parametric methods
The main purpose of this dissertation is to study the most important optimization models to mitigate financial risks. Especially, we want to construct optimal portfoliosusing the concepts of first-order stochastic dominance, second-order stochastic dominance and third-order stochastic dominance as well as the CVaR approach, including three different ...openaire +1 more source