Results 1 to 10 of about 205,425 (288)
Model Independent Expansion History from Supernovae: Cosmology versus Systematics
, 2019 We examine the Pantheon supernovae distance data compilation in a model independent analysis to test the validity of cosmic history reconstructions beyond the concordance $\Lambda$CDM cosmology. Strong deviations are allowed by the data at $z\gtrsim1$ in
Kim, Alex G. +3 more
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Smoothing parameter selection in two frameworks for penalized splines [PDF]
, 2011 There are two popular smoothing parameter selection methods for spline smoothing. First, criteria that approximate the average mean squared error of the estimator (e.g. generalized cross validation) are widely used.
Krivobokova, Tatyana
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Computation and Smoothing Parameter Selection In Penalized Likelihood Regression [PDF]
Communications for Statistical Applications and Methods, 2005 This paper consider penalized likelihood regression with data from exponential family. The fast computation method applied to Gaussian data(Kim and Gu, 2004) is extended to non Gaussian data through asymptotically efficient low dimensional approximations and corresponding algorithm is proposed. Also smoothing parameter selection is explored for various
openaire +1 more source
Robust exponential smoothing of multivariate time series. [PDF]
Multivariate time series may contain outliers of different types. In presence of such outliers, applying standard multivariate time series techniques becomes unreliable. A robust version of multivariate exponential smoothing is proposed.
Croux, Christophe +2 more
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Uncertainty-aware traction force microscopy.
PLoS Computational BiologyTraction Force Microscopy (TFM) is a versatile tool to quantify cell-exerted forces by imaging and tracking fiduciary markers embedded in elastic substrates. The computations involved in TFM are often ill-conditioned, and data smoothing or regularization
Adithan Kandasamy +4 more
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DesimalThe Brown and Holt DES method effectively captures trends in time-series data. Its forecasting accuracy heavily depends on the selection of optimal smoothing parameters. Often, the smoothing parameters are selected manually using trial and error methods.
Chelsea Fatihah Rahma +3 more
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Technical Note: Interference errors in infrared remote sounding of the atmosphere [PDF]
Atmospheric Chemistry and Physics, 2007 Classical error analysis in remote sounding distinguishes between four classes: "smoothing errors," "model parameter errors," "forward model errors," and "retrieval noise errors".
R. Sussmann, T. Borsdorff
doaj
Journal of Sustainable Mining, 2017 The results of marking average courses of subsidence measured on the points of measuring line no. 1 of the “Budryk” Hard Coal Mine, set approximately perpendicularly to a face run of four consecutively mined longwalls in coal bed 338/2 have been ...
Justyna Orwat, Ryszard Mielimąka
doaj +1 more source
Optimal Estimation for the Functional Cox Model
, 2016 Functional covariates are common in many medical, biodemographic, and neuroimaging studies. The aim of this paper is to study functional Cox models with right-censored data in the presence of both functional and scalar covariates. We study the asymptotic
Qu, Simeng, Wang, Jane-Ling, Wang, Xiao
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Bias in nearest-neighbor hazard estimation [PDF]
In nonparametric curve estimation, the smoothing parameter is critical for performance. In order to estimate the hazard rate, we compare nearest neighbor selectors that minimize the quadratic, the Kullback-Leibler, and the uniform loss.
Dette, Holger, Weißbach, Rafael
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