Results 61 to 70 of about 1,132,913 (160)
Accompanied by 4 preliminary ms. map sections of [Geological map of the Commonwealth of Australia] : Coloured geol. map N.S.W., Queensland copy geol. map, New Guinea geological map, [Cross section of North Australia to Tasmania]; Includes Edgeworth David'
David, T. W. Edgeworth (Tannatt William Edgeworth), Sir, 1858-1934.
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Estimation of parameters of finite population L-statistics
We consider the estimation of important parameters of a linear combination of order statistics (L-statistic) in a finite population, emphasizing the influence of auxiliary information on the estimation accuracy.
Dalius Pumputis, Andrius Čiginas
doaj
[German Mine at "The Pimple", Vimy] [cartographic material] .
4th ed. Rev. T W E D, 18.2.17. Includes partially completed legend showing soil types.; Ms. cross-section of German Mine at Vimy by Edgeworth David showing soil type.; Title from accompanying sheet of notes.; Also available in an electronic version via ...
David, T. W. Edgeworth (Tannatt William Edgeworth), Sir, 1858-1934.
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Edition 1, geological. 28 S.W. 1, Kemmel [cartographic material] .
Ms. geological map of Kemmel region, overprinted on Ed. 3 of Ordnance Survey trench map, showing Belgian and British bores, springs and soil type by Edgeworth David.
David, T. W. Edgeworth (Tannatt William Edgeworth), Sir, 1858-1934.
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Non-Gaussian Expansion of Minkowski Tensors in Redshift Space
This paper focuses on extending the use of Minkowski tensors to analyze anisotropic signals in cosmological data, focusing on those introduced by redshift space distortions.
Stephen Appleby +4 more
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At foot of cross-section: Printing Coy. R.E., W.O.B. / 2734.; In upper right corner: Section C.; Includes legend showing soil types and geologic timetable.; Ms. cross-section from Hill 60 "A" Caterpillar to Trench 122 No.
David, T. W. Edgeworth (Tannatt William Edgeworth), Sir, 1858-1934.
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5th-Order Multivariate Edgeworth Expansions for Parametric Estimates
The only cases where exact distributions of estimates are known is for samples from exponential families, and then only for special functions of the parameters. So statistical inference was traditionally based on the asymptotic normality of estimates. To
C. S. Withers
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Photocopy of preliminary ms. geological map by Edgeworth David of part of the Maitland District. Relief shown by hachures.; Electronic reproduction. Canberra : National Library of Australia, 2003. 1 digital map : col.
David, T. W. Edgeworth (Tannatt William Edgeworth), Sir, 1858-1934.
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Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak [PDF]
It is well-known that size-adjustments based on Edgeworth expansions for the t-statistic perform poorly when instruments are weakly correlated with the endogenous explanatory variable.
Gustavo A. Suarez +2 more
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Edgeworth Expansions When the Parameter Dimension Increases with Sample Size
Suppose that we have a statistical model with q unknown parameters w, and an estimate w^, based on a sample of size n. A basic question is: what is the covariance of the estimate? The covariance is needed for the Central Limit Theorem (CLT). This gives a
Christopher Stroude Withers
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