scholarly journals On the Gini measure decomposition

2011 ◽  
Vol 81 (1) ◽  
pp. 133-139 ◽  
Author(s):  
P. Giudici ◽  
E. Raffinetti
Keyword(s):  
Measure Decomposition

Estimating the reduced moments of a random measure

1996 ◽  
Vol 28 (02) ◽  
pp. 335-336
Author(s):  
Kiên Kiêu ◽  
Marianne Mora
Keyword(s):  
Transformation Group ◽  
Smooth Boundary ◽  
Random Measure ◽  
Random Sets ◽  
Random Set ◽  
Counting Measure ◽  
Geometrical Properties ◽  
Measure Decomposition ◽  
Moment Measures ◽  
Curvature Measures

Random measures are commonly used to describe geometrical properties of random sets. Examples are given by the counting measure associated with a point process, and the curvature measures associated with a random set with a smooth boundary. We consider a random measure with an invariant distribution under the action of a standard transformation group (translatioris, rigid motions, translations along a given direction and so on). In the framework of the theory of invariant measure decomposition, the reduced moments of the random measure are obtained by decomposing the related moment measures.

Multidimensional query reformulation with measure decomposition

2018 ◽  
Vol 78 ◽  
pp. 23-39 ◽  
Author(s):  
Claudia Diamantini ◽  
Domenico Potena ◽  
Emanuele Storti
Keyword(s):  
Query Reformulation ◽  
Measure Decomposition

scholarly journals The Production of Organic Matter from Rhizophora mucronata and Sonneratia alba at The Kajhu and Meunasah Mesjid Villages, Aceh Besar

Omni-Akuatika ◽  
2017 ◽  
Vol 13 (1) ◽  
Author(s):  
Mai Suriani ◽  
Dietriech G Bengen ◽  
Tri Prartono
Keyword(s):  
Organic Matter ◽  
Coastal Waters ◽  
Mangrove Ecosystem ◽  
Decay Rates ◽  
Litter Production ◽  
Rhizophora Mucronata ◽  
Decomposition Rates ◽  
Ecological Functions ◽  
Sonneratia Alba ◽  
Measure Decomposition

 Production and decomposition of mangrove litter could contribute organic matter and nutrients to the coastal waters. This study was to estimate the extent to which the rehabilitated mangrove of Rhizophora mucronata and Sonneratia alba contribute organic matter. This study was conducted from November 2015 to January 2016. Litter traps were used to collect the litter production and litterbags to measure decomposition rates. The results showed that the average of litter production for Sonneratia alba and Rhizophora mucronata was 4,38 g.m-2.day-1 and 3,61 g.m-2.day-1, respectively. However, Sonneratia alba apparently showed higher decay rates compare with Rhizophora mucronata. Nutrients element (N and P) released were 321,2 kg.ha-1.years-1 and 47,45 kg.ha-1.years-1 for Sonneratia alba; and 131,4 kg.ha-1.years-1 and 13,14 kg.ha-1.years-1 for Rhizophora mucronata. Overall, this study indicated that the mangrove rehabilitation in the area study contributed insignificantly carbon restocking the affected area, although it was able to provide ecological functions of this mangrove ecosystem.

Estimating the reduced moments of a random measure

1996 ◽  
Vol 28 (2) ◽  
pp. 335-336 ◽  
Author(s):  
Kiên Kiêu ◽  
Marianne Mora
Keyword(s):  
Transformation Group ◽  
Smooth Boundary ◽  
Random Measure ◽  
Random Sets ◽  
Random Set ◽  
Counting Measure ◽  
Geometrical Properties ◽  
Measure Decomposition ◽  
Moment Measures ◽  
Curvature Measures

Random measures are commonly used to describe geometrical properties of random sets. Examples are given by the counting measure associated with a point process, and the curvature measures associated with a random set with a smooth boundary. We consider a random measure with an invariant distribution under the action of a standard transformation group (translatioris, rigid motions, translations along a given direction and so on). In the framework of the theory of invariant measure decomposition, the reduced moments of the random measure are obtained by decomposing the related moment measures.

scholarly journals A general measure decomposition theorem by means of the generalized wallman remainder

1984 ◽  
Vol 36 (1) ◽  
pp. 87-105
Author(s):  
George Bachman ◽  
Panagiotis D. Stratigos
Keyword(s):  
Decomposition Theorem ◽  
General Measure ◽  
Finitely Additive Measures ◽  
Measure Decomposition ◽  
Additive Measures

AbstractLet ℒ be a lattice of subsets of a setX. LetMR(ℒ) denote the set of all ℒ-regular (finitely additive) measures on the algebra generated by ℒ. Under the assumption that ℒ is disjunctive, in the first part of the paper, criteria are obtained for the σ-smoothness, τ-smoothness, and tightness of elements ofMR(ℒ) in terms of the general Wallman remander. in the second part of the paper, various applications are given, and, in particular, extensions and refinements of the Yoside-Hewitt Decom position Theorem are obtained.

Estimating the reduced moments of a random measure

1999 ◽  
Vol 31 (1) ◽  
pp. 48-62 ◽  
Author(s):  
Kiên Kiêu ◽  
Marianne Mora
Keyword(s):  
Invariant Measure ◽  
Stochastic Geometry ◽  
Transformation Group ◽  
Random Measure ◽  
Mixing Condition ◽  
Asymptotic Results ◽  
Unbiased Estimators ◽  
Measure Decomposition ◽  
General Method

We consider a random measure for which distribution is invariant under the action of a standard transformation group. The reduced moments are defined by applying classical theorems on invariant measure decomposition. We present a general method for constructing unbiased estimators of reduced moments. Several asymptotic results are established under an extension of the Brillinger mixing condition. Examples related to stochastic geometry are given.

An induction proof of the generalized Blaschke-Petkantschin formula

1996 ◽  
Vol 28 (2) ◽  
pp. 334-334
Author(s):  
E. B. Vedel Jensen
Keyword(s):  
Lebesgue Measure ◽  
Hausdorff Measure ◽  
Integral Geometry ◽  
Geometric Measure ◽  
Measure Decomposition

The classical Blaschke-Petkanschin formula is a formula in integral geometry givmg a geometric measure decomposition of the q-fold product of Lebesgue measure. The original versions are due to Blaschke and Petkanschin in the 1930s. In Zähle (1990) and Jensen and Kiêu (1992), generalized versions have been derived, where Lebesgue measure is replaced by Hausdorff measure.

scholarly journals Ocean temperature controls kelp decomposition and carbon sink potential

2020 ◽  
Author(s):  
Karen Filbee-Dexter ◽  
Colette Feehan ◽  
Dan Smale ◽  
Kira Krumhansl ◽  
Skye Augustine ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Field Experiments ◽  
Carbon Sink ◽  
Mitigation Strategies ◽  
Climate Mitigation ◽  
Ocean Temperature ◽  
Decomposition Rates ◽  
Measure Decomposition ◽  
Northern Regions ◽  
New Evidence

Abstract Compelling new evidence shows that kelp production contributes an important and underappreciated flux of carbon in the ocean. Major questions remain, however, about the controls on the cycling of this organic carbon in the coastal zone, and their implications for future carbon sequestration. Here we used field experiments distributed across 28° latitude, and the entire range of two dominant kelps in the northern hemisphere, to measure decomposition rates of kelp detritus on the seafloor in relation to environmental factors. Ocean temperature was the strongest control on detritus decomposition in both species, and it was positively related to decomposition. This suggests that decomposition could accelerate with ocean warming under climate change, increasing remineralization and reducing overall kelp carbon sequestration. However, we also demonstrate the potential for high kelp-carbon storage in cooler (northern) regions, which could be targeted by climate mitigation strategies to expand blue carbon sinks.

scholarly journals POLAR DECOMPOSITION OF THE k-FOLD PRODUCT OF LEBESGUE MEASURE ON ℝn

2012 ◽  
Vol 85 (2) ◽  
pp. 315-324 ◽  
Author(s):  
S. REZA MOGHADASI
Keyword(s):  
Lebesgue Measure ◽  
Polar Decomposition ◽  
Rotational Symmetry ◽  
Orthogonal Transformation ◽  
Geometric Measure ◽  
Measure Decomposition

AbstractThe Blaschke–Petkantschin formula is a geometric measure decomposition of the q-fold product of Lebesgue measure on ℝn. Here we discuss another decomposition called polar decomposition by considering ℝn×⋯×ℝn as ℳn×k and using its polar decomposition. This is a generalisation of the Blaschke–Petkantschin formula and may be useful when one needs to integrate a function g:ℝn×⋯×ℝn→ℝ with rotational symmetry, that is, for each orthogonal transformation O,g(O(x1),…,O(xk))=g(x1,…xk). As an application we compute the moments of a Gaussian determinant.

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