Behrens-Fisher problem

Behrens-Fisher problem - Factbites
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Topic: Behrens-Fisher problem

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	Fiducial - Wikipedia, the free encyclopedia
		In statistics, fiducial inference is a form of interval estimation developed by Ronald Fisher in connection with the Behrens-Fisher problem.
		In physics and 3D computer graphics, fiducials are reference points: fixed points or lines within a scene to which other objects can be related or to which objects can be measured against.
		In applications of augmented reality or virtual reality, fiducials are often manually applied to objects in the scenery to recognize these objects in images of the scenery.
	en.wikipedia.org /wiki/Fiducial (228 words)

	SAS Tips, Tricks, and Licks
		The Welch test is an approximate test, since in the case of two samples from respective Gaussian distributions with unequal variances, an exact t-test does not exist (known as the Behrens-Fisher problem).
		The p-values for the Chi-Square test, The Likelihood Ratio Test (sometimes called the G or G2 test), and Fisher's Exact Test are highlighted.
		However, the Chi-Square tests are identical to the Z-tests, since a squared standard Gaussian random variable is equivalent to a Chi-Square random variable with a single degree of freedom and this test has exactly 1 degree of freedom.
	home.nc.rr.com /schabenb/SASTips.htm (228 words)

	Courses
		Sampling theory and its critique, subjective probability, likelihood principles, Bayes theorem, Bayesian analysis of Normal theory inference problems, the Behrens-Fisher problem, assessment of model assumptions, robustness of inference, analysis of variance, estimation of variance components, empirical Bayes, some aspects of multivariate problems.
		Conditioning, distribution theory, approximation to distributions, modes of convergence, limit theorems, statistical models, parameter estimation, comparison of estimators, confidence sets, theory of hypothesis tests, introduction to Bayesian inference and nonparametric estimation.
		Elements of probability, important discrete distributions, acceptance sampling by attributes, sample characteristics, probability distributions and population characteristics, the normal distribution, acceptance sampling plans based on sample means and variances, sampling from the normal, the central limit theorem, point and interval estimation.
	www.wisc.edu /grad/catalog/letsci/statisC.html (228 words)

	Articles Authored by G. Jogesh Babu
		Babu, G. J.; Padmanabhan, A. Re-sampling methods for the non-parametric Behrens-Fisher problem.
		Statistics and Probability: A Raghu Raj Bahadur Festscrift, 63-71, J. Ghosh, S. Mitra, K. Parthasarathy and B. Prakasa Rao (Eds.), Wiley Eastern Limited, New Delhi, 1993.
		Babu, G. A note on the bootstrapped empirical process.
	www.stat.psu.edu /~babu/res_pub.html (228 words)

	bfsolv.txt
		1 1 AN ADJUSTED LIKELIHOOD RATIO ALGORITHM FOR THE BEHRENS-FISHER PROBLEM HAMPARSUM BOZDOGAN AND DONALD E. The following subroutines are from the IMSL package: UERSET MDTD MDCH ************************************************************************
	www.math.virginia.edu /~der/pdf/bfsolv.txt (28 words)

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Topic: Behrens-Fisher problem

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