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LINEAR REGRESSION WITH NON-NORMAL ERRORS
Advances and Applications in Statistics, 2018Summary: We explain how to find an accurate approximation of the sampling distribution of ML estimators relating to simple linear regression with non-normal errors. Using Edgeworth series, our method achieves a substantially better accuracy than the usual normal approximation, based on Fisher information matrix.
Li, Na, Vrbik, Jan
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1983
In the literature, several very natural modal logics have been studied that are weaker than those we have considered thus far. In this chapter we want to take a look at some of them. (For our present purposes, we may think of a modal logic L simply as a certain set of modal formulas, called L-valid, or L-theorems.
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In the literature, several very natural modal logics have been studied that are weaker than those we have considered thus far. In this chapter we want to take a look at some of them. (For our present purposes, we may think of a modal logic L simply as a certain set of modal formulas, called L-valid, or L-theorems.
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NON-NORMAL GRAPHS OF FINITE GROUPS
Journal of Algebra and Its Applications, 2013Let G be a finite group and H be a subgroup of G. We introduce the non-normal graph of H in G, denoted by [Formula: see text]H,G, and give some of the graph theoretical properties of [Formula: see text]H,G.
Farrokhi D. G., M. +2 more
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On non‐normal del Pezzo surfaces
Mathematische Nachrichten, 2003AbstractLetYbe a non‐normal del Pezzo surface over ℂ and letd≔ (ω−1Y)2> 0 be the degree ofY. Then we prove thatω⊗d−4Yis very ample ford= 1, 2.
Abe, Makoto, Furushima, Mikio
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Bol loops with non-normal nuclei
Archiv der Mathematik, 2003The purpose of this note is to present a large class of Bol loops with nonnormal nuclei. Such class is obtained by means of the following construction: given a group \(H\), a loop \(K\) and a homomorphism \(\Theta\colon K\to\Aut(H)\), then \(L:=H\times K\) becomes a loop together with the following binary operation: \[ (h_1,k_1)(h_2,k_2):=(h_1\Theta_ ...
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Prior data for non‐normal priors
Statistics in Medicine, 2007AbstractData augmentation priors facilitate contextual evaluation of prior distributions and the generation of Bayesian outputs from frequentist software. Previous papers have presented approximate Bayesian methods using 2×2 tables of ‘prior data’ to represent lognormal relative‐risk priors in stratified and regression analyses.
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1995
A fundamental question in a quality organisation is “Are we capable of delivering what the customer wants?”. To be able to answer this question we need to bring together precise specifications of what the customer wants and what we can deliver.
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A fundamental question in a quality organisation is “Are we capable of delivering what the customer wants?”. To be able to answer this question we need to bring together precise specifications of what the customer wants and what we can deliver.
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