scholarly journals Cross-correlation methods for surface photometry: two-component models

1992 ◽  
Vol 256 (4) ◽  
pp. 673-678 ◽  
Author(s):  
S. Phillipps ◽  
P. J. Boyce
Keyword(s):  
Cross Correlation ◽  
Surface Photometry ◽  
Correlation Methods ◽  
Two Component ◽  
Component Models

scholarly journals Validity of two-component models for estimating body fat of black men

2001 ◽  
Vol 90 (2) ◽  
pp. 649-656 ◽  
Author(s):  
Dale R. Wagner ◽  
Vivian H. Heyward
Keyword(s):  
Black Men ◽  
Body Fat ◽  
Predictive Accuracy ◽  
Component Model ◽  
Suitable Alternative ◽  
Heterogeneous Sample ◽  
Four Component Model ◽  
Two Component ◽  
Model Conversion ◽  
Component Models

Commonly used two-component model conversion formulas that estimate relative body fat (%BF) from body density (Db) were cross-validated on a heterogeneous sample of black men ( n = 30; age = 19–45 yr). A four-component model was used to obtain criterion measures of %BF, and linear regression and analysis of individual residual scores were conducted to assess the predictive accuracy of the formulas under investigation. The two-component formula commonly used to estimate %BF of black men (Schutte JE, Townsend EJ, Hugg J, Shoup RF, Malina RM, and Blomqvist CG. J Appl Physiol 56: 1647–1649, 1984) significantly ( P ≤ 0.01) and systematically (87% of sample) overestimated %BF (−1.28%); thus we developed the following two-component Db conversion formula: %BF = [(4.858/Db) − 4.394] × 100. Because our formula was derived from a four-component model and a larger, more heterogeneous sample than the commonly used two-component formula, we recommend using it to convert Db to %BF for black men. Additionally, there was good agreement between dual-energy X-ray absorptiometry and the four-component model, making this a suitable alternative for estimating the %BF of black men.

scholarly journals Analysis of Pole Position from 1846 to 1970

1972 ◽  
Vol 48 ◽  
pp. 19-32 ◽  
Author(s):  
E. M. Gaposchkin
Keyword(s):  
Data Analysis ◽  
Historical Data ◽  
Pole Position ◽  
Point Of View ◽  
Two Component ◽  
Component Motion ◽  
Component Models

One- and two-component models for the Chandler motion are investigated with the use of historical data. Evidence for a two-component motion is more convincing from both the data-analysis and the geophysical point of view.

Statistical Analysis of Price Volatility of Agricultural Commodities Traded at the Ethiopian Commodity Exchange (ECX) Using Multiplicative GARCH-MIDAS Two-component Model

2020 ◽  
pp. 097215091989562
Author(s):  
Teshome Hailemeskel Abebe ◽  
Emmanuel Gabreyohannes Woldesenbet ◽  
Belaineh Legesse Zeleke
Keyword(s):  
Price Volatility ◽  
Absolute Error ◽  
Fuel Oil ◽  
Component Model ◽  
Real Effective Exchange Rate ◽  
Time Varying ◽  
Data Sampling ◽  
Commodity Exchange ◽  
Two Component ◽  
Component Models

We applied multiplicative GARCH-MIDAS two component models for price return volatility of selected commodities traded at the Ethiopian commodity exchange (ECX). Unlike the ‘traditional’ generalized autoregressive conditional heteroscedasticity (GARCH) family models, GARCH-MIDAS component model can capture the time-varying conditional as well as unconditional volatilities, and accommodates macroeconomic variables observed at different frequencies through mixed interval data sampling (MIDAS) specification. The results of our specification tests revealed the existence of both time-varying conditional and unconditional variance. The fitted GARCH-MIDAS component models showed that realized volatility, inflation rate and fuel oil price have had an increasing effect on the price volatility of the commodities under consideration, while real effective exchange rate (REER) had the opposite effect. Furthermore, mean square error (MSE), mean absolute error (MAE) and Diebold and Mariano (DM) test were used for evaluating and comparing the forecasting ability of GARCH-MIDAS component models against standard GARCH models. The results revealed that GARCH-MIDAS component models outperformed the standard GARCH model for high-frequency data.

scholarly journals On BLR Size Estimates in Reverberation Models

2009 ◽  
Vol 5 (S267) ◽  
pp. 209-209
Author(s):  
Alexander V. Melnikov ◽  
Ivan I. Shevchenko
Keyword(s):  
Emission Line ◽  
Cross Correlation ◽  
Light Curves ◽  
Time Lags ◽  
Broad Line ◽  
Broad Line Region ◽  
Correlation Methods ◽  
Line Region ◽  
Size Estimates

Following the approach of Melnikov & Shevchenko (2008), we explore how the nonlinearity in the emission-line luminosity Ll of a broad-line region cloud, in its dependence on the ionizing continuum flux Fi incident on the cloud, affects estimates of the size of the broad-line region by means of cross-correlation methods. We show that the estimates obtained by straightforward cross-correlation of emission-line and continuum light curves can significantly underestimate the BLR size. We demonstrate examples of direct reverberation modelling of AGN emission-line light curves taking into account the nonlinearity of the “Ll–Fi” relation. This nonlinearity allows one to explain the differences in the time lags for different lines. Cross-correlation estimates of the BLR size turn out to be small in comparison to the estimates obtained by the direct reverberation modelling.

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