Search Results

You are looking at 1 - 10 of 11 items for :

  • Earth and Environmental Sciences x
  • All content x
Clear All
Central European Geology
Authors: Attila Demény, Gabriella Schöll-Barna, Pál Sümegi, Péter Sipos, István Fórizs, Brigitta Réka Balázs, Bernadett Bajnóczi, and Gordon Cook

1999 The North Atlantic's l2 kyr Climate Rhythm: Relation to Heinrich Events, Dansgaard/Oeschger Cyles and the Little Ice Age KeigwinMechanisms of Global Climate Change at Millennial Time Scales. — Geophysical

Restricted access

( ℓ ) − X ¯ ( ) ) 2 ,   ℓ = 1 ,   2 , … ,   N , (2) In Eq.  (2) , the upper index ( ℓ ) shows that the expression goes for the first ℓ realizations. From the above variance decomposition, WGV and BGV take the following forms for

Open access
Central European Geology
Authors: Ildikó Gyollai, Ákos Kereszturi, and Elias Chatzitheodoridis

.08 0.83 b. d. l. 2.72 1.99 0.81 CaO 0

Open access

-UE WP4 L2 Report, IZIIS, Skopje Trendafiloski G. S. Code based approach, Case study: Aseismic Design Codes in Macedonia 2002

Restricted access

A new L 2 norm joint inversion technique is presented and combined with the series expansion inversion method applied for different simulated erroneous Vertical Electric Sounding (VES) data sets over a complicated two dimensional structure. The applied joint inversion technique takes into consideration the complete form of the likelihood function. As a result there is no need to apply input weights to the individual objective functions. The model consists of three layers with homogeneous resistivities. The first layer boundary is a horizontal plane, the other is a two dimensional laterally varying surface. For the VES inversion the exact data sets were calculated by finite difference method, one in strike direction and the other in dip direction. These data sets were contaminated with normally distributed random errors. During inversion the second layer boundary function was determined. For comparison individual and joint inversion examples were calculated for the two data sets. The best model parameter estimate result was produced by the method of automated weighting.

Restricted access

In the present paper 9 error characteristics are detailedly investigated by Monte Carlo calculations in point of view of the fluctuation of their estimates. In all 9 cases the error characteristic is defined as the minimum value of a modern norm of deviations, just in the same manner as in the classical statistics the s scatter was defined as the minimum value of the L 2-norm. The results are in Table I summarized and in Figs 1-9 presented for five parent distribution types and for five sample sizes: n = 5; 9; 25; 100 and 400; the statistical fluctuation is characterized by the relative semi-intersextile ranges of the minimum norms (N = 200000 repetition number was chosen in the Monte Carlo calculations). On the basis of the values of Table I the uncertainties can be determined with such accuracy which is seldom required in the practice. Because of the fact that ordinarily 15-20% is accepted as the "error of the error", in the Table III asymptotic values are also given to give possibility to the simplest: according to A asympt/vn executed calculations.

Restricted access

In the region of the Carpathian-Pannonian Basin (44–50N; 13–28E) 81 earthquakes have moment magnitude (M w); 61 of them are crustal events (focal depth <65 km) while 20 earthquakes belong to the intermediate focal depth region of the Vrancea (Romania) zone. For crustal events the regression of moment magnitude (M w) on local magnitude (M l) shows a better fit for large magnitudes using a second order equation against to a linear relationship, and the actual quadratic formula based on 61 events is the following: \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{upgreek} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \pagestyle{empty} \DeclareMathSizes{10}{9}{7}{6} \begin{document} $\begin{gathered} M_w = 1.37( \pm 0.28) + 0.39( \pm 0.18)M_l + 0.061( \pm 0.026)M_l^2 \hfill \\ (M_w :1.9 - 5.5;M_l :1.4 - 5.5). \hfill \\ \end{gathered} $ \end{document}.In the intermediate focal depth Vrancea zone of the south-eastern bend of the Carpathians (44.5–46.5N; 25.5–28.0E) the number of body wave magnitudes is the largest one (20) among the local (8), the surface wave (14) and the duration (17) magnitudes. The linear relationship between the moment (M w) and the body wave (M b) magnitudes has the following form: \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{upgreek} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \pagestyle{empty} \DeclareMathSizes{10}{9}{7}{6} \begin{document} $M_w = 1.20( \pm 0.08)M_b - 0.76( \pm 0.40)(M_w :4.1 - 7.7;M_b :3.8 - 7.3).$ \end{document}.The relationships of the different (M l, M s, M b, M d) magnitudes are also presented in the paper.

Restricted access

As the variance (the square of the minimum L 2-norm, i.e., the square of the scatter) is one of the basic characteristics of the conventional statistics, it is of practical importance to know the errors of its determination for different parent distribution types. This statement is outstandingly valid for the geostatistics because the (h) variogram (called also as semi-variogram) is defined as the half variance of some quantity-difference (e.g. difference of ore concentrations) in function of the h dis- tance of the measuring points and this g (h)-curve plays a basic role in the classical geostatistics. If the scatter (s VAR) is chosen to characterize the determination uncertainties of the variance (denoted the latter by VAR), this can be easily calculate as the quotient A VAR= Ön (if the number n of the elements in the sample is large enough); for the so-called asymptotic scatter A VAR is known a simple formula (containing the fourth moment). The present paper shows that the AVAR has finite value unfortunately only for about a quarter of distribution types occurring in the earth sciences, it must be especially accentuate that A VAR has infinite value for that distribution type which most frequent occurs in the geostatistics. It is proven by the present paper that the law of large numbers is always fulfilled (i.e., the error always decreases if n increases) for the error-determinations if the semi-intersextile range is accepted (instead of the scatter); the single (quite natural) condition is the existence of the theoretical variance for the parent distribution. __

Restricted access

P -norms compared to that of the L 2 -norm with respect to the simultaneously achieved accuracy in the space- and frequency-domain. Acta Geod. Geoph. Hung. , 30, 293–299. Hajagos B

Restricted access

--312. Hajagos B, Steiner F 2000: The fulfilment of the law of large numbers for arithmetic means in case of infinite asymptotic scatter. Acta Geod. Geoph. Hung. , 35, 4, 453--464. Steiner F 2000: Comparison of the L 2 , L 1 - and P

Restricted access