Switched-mode power supply applications: Difference between revisions

From formulasearchengine
Jump to navigation Jump to search
Newer edit →
Spelling
 
en>Dsimic
Removed a few useless pictures; Layout improvements
Line 1: Line 1:
I'm Fausto (19) from Wolfpassing An Der Hochleithen, Austria. <br>I'm learning Portuguese literature at a local high school and I'm just about to graduate.<br>I have a part time job in a backery.<br><br>Also visit my web-site ... [http://www.healthinsuredirect.com/low-cost-health-insurance Low cost health insurance plans]
In [[statistics]], '''Hoeffding's test of independence''', named after [[Wassily Hoeffding]], is a test based on the population measure of deviation from independence
 
:<math>H = \int (F_{12}-F_1F_2)^2 \, dF_{12} \!</math>
 
where <math>F_{12}</math> is the [[joint distribution function]] of two random variables, and <math>F_1</math> and <math>F_2</math> are their [[marginal distribution]] functions.
Hoeffding derived an [[unbiased estimator]] of <math>H</math> that can be used to test for [[independence (probability theory)|independence]], and is [[consistent estimator|consistent]] for any continuous [[alternative hypothesis|alternative]]. The test should only be applied to data drawn from a [[continuous probability distribution|continuous distribution]], since <math>H</math> has a defect for discontinuous <math>F_{12}</math>, namely that it is not necessarily zero when <math>F_{12}=F_1F_2</math>.
 
A recent paper<ref>Wilding, G.E., Mudholkar, G.S. (2008) [http://www.sciencedirect.com/science/article/B7CRS-4PJ04Y7-1/2/e10c0f978e665a0d5ffd41a594f9a9ba "Empirical approximations for Hoeffding's test of bivariate independence using two Weibull extensions"], ''Statistical Methodology'', 5 (2), 160-&ndash;170</ref> describes both the calculation of a sample based version of this measure for use as a test statistic, and calculation of the null distribution of this test statistic.
 
==See also==
 
{{Portal|Statistics}}
* [[Correlation]]
* [[Kendall's tau]]
* [[Spearman's rank correlation coefficient]]
*[[Distance correlation]]
 
==Notes==
{{Reflist}}
 
==Primary sources==
* Wassily Hoeffding, A non-parametric test of independence, ''Annals of Mathematical Statistics'' '''19''': 293&ndash;325, 1948. ([http://www.jstor.org/stable/2236021 JSTOR])
* Hollander and Wolfe, Non-parametric statistical methods (Section 8.7), 1999. Wiley.
 
{{DEFAULTSORT:Hoeffding's Independence Test}}
[[Category:Covariance and correlation]]
[[Category:Non-parametric statistics]]
[[Category:Statistical tests]]
[[Category:Statistical dependence]]
 
 
{{statistics-stub}}

Revision as of 23:48, 28 November 2013

In statistics, Hoeffding's test of independence, named after Wassily Hoeffding, is a test based on the population measure of deviation from independence

H=∫(F12−F1F2)2dF12

where F12 is the joint distribution function of two random variables, and F1 and F2 are their marginal distribution functions. Hoeffding derived an unbiased estimator of H that can be used to test for independence, and is consistent for any continuous alternative. The test should only be applied to data drawn from a continuous distribution, since H has a defect for discontinuous F12, namely that it is not necessarily zero when F12=F1F2.

A recent paper[1] describes both the calculation of a sample based version of this measure for use as a test statistic, and calculation of the null distribution of this test statistic.

See also

Sportspersons Hyslop from Nicolet, usually spends time with pastimes for example martial arts, property developers condominium in singapore singapore and hot rods. Maintains a trip site and has lots to write about after touring Gulf of Porto: Calanche of Piana.

Notes

43 year old Petroleum Engineer Harry from Deep River, usually spends time with hobbies and interests like renting movies, property developers in singapore new condominium and vehicle racing. Constantly enjoys going to destinations like Camino Real de Tierra Adentro.

Primary sources

  • Wassily Hoeffding, A non-parametric test of independence, Annals of Mathematical Statistics 19: 293–325, 1948. (JSTOR)
  • Hollander and Wolfe, Non-parametric statistical methods (Section 8.7), 1999. Wiley.


I am Chester from Den Haag. I am learning to play the Cello. Other hobbies are Running.

Also visit my website: Hostgator Coupons - dawonls.dothome.co.kr -

  1. ↑ Wilding, G.E., Mudholkar, G.S. (2008) "Empirical approximations for Hoeffding's test of bivariate independence using two Weibull extensions", Statistical Methodology, 5 (2), 160-–170
Retrieved from "https://en.formulasearchengine.com/index.php?title=Switched-mode_power_supply_applications&oldid=25607"