Results 31 to 40 of about 286,227 (342)
Asymptotics for penalized additive B-spline regression [PDF]
, 2011 This paper is concerned with asymptotic theory for penalized spline estimator in bivariate additive model. The focus of this paper is put upon the penalized spline estimator obtained by the backfitting algorithm.
Naito, K., Yoshida, T.
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Synthesized randomized response techniques
Scientific African, 2023 Reducing response bias in survey research is important in ensuring that the data collected accurately represents the population of interest. This study proposes the synthesized random response technique (SRRT) estimator as an efficient method to reduce ...
Isaac O. Adeniyi, Olusegun S. Ewemooje
doaj
Dynamic Capital Structure Adjustment: Which estimator yields consistent and efficient estimates?
Journal of Economic and Financial Sciences, 2016 The partial adjustment model is key to a number of corporate finance research areas. The model is by its nature an autoregressive-distributed lag model that is characterised by heterogeneity among individuals and autocorrelation due to the presence of ...
Vusani Moyo
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Data Science Journal, 2009 This paper suggests a ratio-cum-product estimator of finite population mean using a correlation coefficient between study variate and auxiliary variate in stratified random sampling.
Rajesh Tailor
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A fixed count sampling estimator of stem density based on a survival function
Journal of Forest Science, 2015 In fixed count sampling (FCS) a fixed number (k) of observations is made at n randomly selected sample locations. For estimation of stem density, the distance from a random sample location to the k nearest trees was measured.
S. Magnussen
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Bias in Nonlinear Estimation [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1971 Summary Although it is widely recognized that maximum-likelihood estimates of the parameters in non-linear models are generally biased, little work appears to have been done on quantitatively assessing these biases. In this paper the difficulties of exact calculation of the bias for a simple example are first illustrated, after which a ...
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On the Bias of Directed Information Estimators [PDF]
2019 IEEE International Symposium on Information Theory (ISIT), 2019 When estimating the directed information between two jointly stationary Markov processes, it is typically assumed that the recipient of the directed information is itself Markov of the same order as the joint process. While this assumption is often made explicit in the presentation of such estimators, a characterization of when we can expect the ...
Gabriel Schamberg, Todd P. Coleman
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Global Polynomial Kernel Hazard Estimation
Revista Colombiana de EstadísticaThis paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator.
MUNIR HIABU +5 more
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A light weight regularization for wave function parameter gradients in quantum Monte Carlo
AIP Advances, 2020 The parameter derivative of the expectation value of the energy, ∂E/∂p, is a key ingredient in variational Monte Carlo (VMC) wave function optimization methods.
Shivesh Pathak, Lucas K. Wagner
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Estimating the bias of a noisy coin [PDF]
AIP Conference Proceedings, 2012 10 ...
Robin Blume-Kohout, Christopher Ferrie
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