Results 11 to 20 of about 538,072 (320)
Spectral Analysis of Stationary Random Bivariate Signals [PDF]
IEEE Transactions on Signal Processing, 2017 A novel approach towards the spectral analysis of stationary random bivariate signals is proposed. Using the Quaternion Fourier Transform, we introduce a quaternion-valued spectral representation of random bivariate signals seen as complex-valued sequences.
Flamant, Julien +2 more
openaire +6 more sources
PREDICTING THE DEPOSITIONAL ENVIRONMENTS AND TRANSPORTATION MECHANISMS OF SEDIMENTS USING GRANULOMETRIC PARAMETERS, BIVARIATE AND MULTIVARIATE ANALYSES [PDF]
GeoScience Engineering, 2019 Grain size distribution and classes present in sedimentary rocks are responsive to the physical changes of the transporting media and the basin of deposition.
P. R. IKHANE, O.V. OLADIPO, O.O. OYEBOLU
doaj +3 more sources
Nonlinear analysis of bivariate data with cross recurrence plots [PDF]
, 2002 We use the extension of the method of recurrence plots to cross recurrence plots (CRP) which enables a nonlinear analysis of bivariate data. To quantify CRPs, we develop further three measures of complexity mainly basing on diagonal structures in CRPs ...
Norbert Marwan, Jürgen Kurths
openalex +6 more sources
Bivariate Marker Measurements and ROC Analysis [PDF]
Biometrics, 2012 SummaryThis article considers receiver operating characteristic (ROC) analysis for bivariate marker measurements. The research interest is to extend tools and rules from univariate marker to bivariate marker setting for evaluating predictive accuracy of markers using a tree‐based classification rule. Using an and–or classifier, an ROC function together
Mei Cheng Wang, Shanshan Li
openaire +3 more sources
Functional Location-Scale Model to Forecast Bivariate Pollution Episodes
Mathematics, 2020 Predicting anomalous emission of pollutants into the atmosphere well in advance is crucial for industries emitting such elements, since it allows them to take corrective measures aimed to avoid such emissions and their consequences.
Manuel Oviedo-de La Fuente +2 more
doaj +1 more source
Remote Sensing, 2023 Bivariate data-driven methods have been widely used in landslide susceptibility analysis. However, the names, principles, and correlations of bivariate methods are still confused.
Langping Li, Hengxing Lan
doaj +1 more source
Genes influencing milk production traits predominantly affect one of four biological pathways
Genetics Selection Evolution, 2008 In this study we introduce a method that accounts for false positive and false negative results in attempting to estimate the true proportion of quantitative trait loci that affect two different traits.
Goddard Michael +2 more
doaj +1 more source
Evaluation and comparison of bivariate and multivariate statistical methods for landslide susceptibility mapping (case study: Zab Basin) [PDF]
, 2012 Landslides are among the great destructive factors which cause lots of fatalities and financial losses all over the world every year. Studying of the factors affecting occurrence of landslides in a region and zoning the resulting damages will certainly ...
Ahmad, Baharin, Khezri, S., Shahabi, H.
core +1 more source
A Bayesian-Model-Averaging Copula Method for Bivariate Hydrologic Correlation Analysis
Frontiers in Environmental Science, 2022 A Bayesian-model-averaging Copula (i.e., BMAC) approach was proposed for correlation analysis of monthly rainfall and runoff in Xiangxi River watershed, China. The BMAC approach was formulated by incorporating existing Bayesian model averaging (i.e., BMA)
Yizhuo Wen +3 more
doaj +1 more source
Time–frequency analysis of bivariate signals
Applied and Computational Harmonic Analysis, 2019 Many phenomena are described by bivariate signals or bidimensional vectors in applications ranging from radar to EEG, optics and oceanography. The time-frequency analysis of bivariate signals is usually carried out by analyzing two separate quantities, e.g. rotary components.
Flamant, Julien +2 more
openaire +6 more sources