Results 11 to 20 of about 9,847,496 (288)
Weakly dependent functional data [PDF]
, 2010 Functional data often arise from measurements on fine time grids and are obtained by separating an almost continuous time record into natural consecutive intervals, for example, days.
Hörmann, Siegfried, Kokoszka, Piotr
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Online Forecast Combination for Dependent Heterogeneous Data [PDF]
, 2007 This paper studies a procedure to combine individual forecasts that achieve theoretical optimal performance. The results apply to a wide variety of loss functions and no conditions are imposed on the data sequences and the individual forecasts apart from
Sancetta, Alessio
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Analysis and equalization of data-dependent jitter [PDF]
, 2006 Data-dependent jitter limits the bit-error rate (BER) performance of broadband communication systems and aggravates synchronization in phase- and delay-locked loops used for data recovery.
Buckwalter, James F., Hajimiri, Ali
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Nonparametric analysis of the time structure of seismicity in a geographic region
Annals of Geophysics, 2002 As an alternative to traditional parametric approaches, we suggest nonparametric methods for analyzing temporal data on earthquake occurrences. In particular, the kernel method for estimating the hazard function and the intensity function are presented ...
A. Quintela-del-Río +2 more
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Strong consistency of a kernel-based rule for spatially dependent data [PDF]
Arab Journal of Mathematical Sciences, 2020 We consider the kernel-based classifier proposed by Younso (2017). This nonparametric classifier allows for the classification of missing spatially dependent data. The weak consistency of the classifier has been studied by Younso (2017).
Ahmad Younso, Ziad Kanaya, Nour Azhari
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Review, 2007 A speech at the Middle Tennessee State University, Annual Economic Outlook Conference, Murfreesboro, Tenn., Sept.
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Dependent Functional Data [PDF]
ISRN Probability and Statistics, 2012 This paper reviews recent research on dependent functional data. After providing an introduction to functional data analysis, we focus on two types of dependent functional data structures: time series of curves and spatially distributed curves. We review statistical models, inferential methodology, and possible extensions.
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Massive data compression for parameter-dependent covariance matrices [PDF]
, 2017 We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated datasets that are required to estimate the covariance matrix required for the analysis of gaussian-distributed data.
de Mijolla, Damien +3 more
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Gamma Kernel Estimation of the Density Derivative on the Positive Semi-Axis by Dependent Data
Revstat Statistical Journal, 2016 We estimate the derivative of a probability density function defined on [0,∞). For this purpose, we choose the class of kernel estimators with asymmetric gamma kernel functions.
L.A. Markovich
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Direction Dependent Background Fitting for the Fermi GBM Data [PDF]
, 2013 We present a method for determining the background of Fermi GBM GRBs using the satellite positional information and a physical model. Since the polynomial fitting method typically used for GRBs is generally only indicative of the background over ...
Bagoly, Zsolt +4 more
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