CSEM and MT data sensitivity analysis for 1D anisotropic inversions

2010 ◽  
Author(s):  
E. Medina ◽  
A. Lovatini ◽  
M. D. Watts
Keyword(s):  
Sensitivity Analysis ◽  
Data Sensitivity

Missing data sensitivity analysis for recurrent event data using controlled imputation

2014 ◽  
Vol 13 (4) ◽  
pp. 258-264 ◽  
Author(s):  
Oliver N. Keene ◽  
James H. Roger ◽  
Benjamin F. Hartley ◽  
Michael G. Kenward
Keyword(s):  
Sensitivity Analysis ◽  
Missing Data ◽  
Recurrent Event ◽  
Event Data ◽  
Recurrent Event Data ◽  
Data Sensitivity

APPLICATION OF RELEVANCE VECTOR MACHINE IN SEISMIC ATTENUATION PREDICTION

2007 ◽  
Vol 01 (04) ◽  
pp. 299-309 ◽  
Author(s):  
PIJUSH SAMUI
Keyword(s):  
Sensitivity Analysis ◽  
Information Content ◽  
Relevance Vector Machine ◽  
Seismic Attenuation ◽  
Rock Properties ◽  
Input Parameters ◽  
Practical Tool ◽  
Data Sensitivity

The recently introduced relevance vector machine (RVM) technique is applied to predict seismic attenuation based on rock properties. The RVM provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. It evades complexity by producing models that have structure and as a result parameterization process that is appropriate to the information content of the data. Sensitivity analysis has been also performed to investigate the importance of each of the input parameters. The results show that RVM approach has the potential to be a practical tool for determination of seismic attenuation.

scholarly journals Airfoil data sensitivity analysis for actuator disc simulations used in wind turbine applications

2014 ◽  
Vol 524 ◽  
pp. 012135 ◽  
Author(s):  
Karl Nilsson ◽  
Simon-Philippe Breton ◽  
Jens N Sørensen ◽  
Stefan Ivanell
Keyword(s):  
Sensitivity Analysis ◽  
Wind Turbine ◽  
Actuator Disc ◽  
Data Sensitivity

scholarly journals RNA-Seq vs Dual- and Single-Channel Microarray Data: Sensitivity Analysis for Differential Expression and Clustering

PLoS ONE ◽  
2012 ◽  
Vol 7 (12) ◽  
pp. e50986 ◽  
Author(s):  
Alina Sîrbu ◽  
Gráinne Kerr ◽  
Martin Crane ◽  
Heather J. Ruskin
Keyword(s):  
Sensitivity Analysis ◽  
Differential Expression ◽  
Microarray Data ◽  
Single Channel ◽  
Rna Seq ◽  
Data Sensitivity

INFLATION, LIQUIDITY, AND LONG-RUN GROWTH

2016 ◽  
Vol 23 (2) ◽  
pp. 888-906 ◽  
Author(s):  
Ge Zhou
Keyword(s):  
Economic Growth ◽  
Sensitivity Analysis ◽  
Financial Development ◽  
Investment Projects ◽  
Long Run ◽  
The Us ◽  
The Impact ◽  
Positive Effect ◽  
Data Sensitivity ◽  
Effect On Growth

This paper revisits the long-run relationship between inflation and economic growth by exploring the impact of inflation on investment. I illustrate that inflation may have a positive effect on growth by mitigating the liquidity risks of investment projects. Together with the traditional effect of the “inflation tax” on investment, a hump-shaped relationship between inflation and economic growth can be obtained in a calibrated model, which is consistent with the US postwar data. Sensitivity analysis suggests that the degree of financial development and the magnitude of the aggregate liquidity demand help explain the mixed empirical findings.

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