Results 31 to 40 of about 304,459 (351)

Bias in Nonlinear Estimation

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 ...
openaire   +2 more sources

Prewhitening Bias in HAC Estimation* [PDF]

Oxford Bulletin of Economics and Statistics, 2005
AbstractHeteroskedasticity and autocorrelation consistent (HAC) estimation commonly involves the use of prewhitening filters based on simple autoregressive models. In such applications, small sample bias in the estimation of autoregressive coefficients is transmitted to the recolouring filter, leading to HAC variance estimates that can be badly biased.
Donggyu Sul, Peter C.B. Phillips, Choi, Chi-Young   +2 more
openaire   +2 more sources

A note on multiple imputation for method of moments estimation [PDF]

, 2015
Multiple imputation is a popular imputation method for general purpose estimation. Rubin(1987) provided an easily applicable formula for the variance estimation of multiple imputation.
Kim, Jae Kwang, Kim, Jae Kwang, Yang, Shu   +2 more
core   +4 more sources

Global Polynomial Kernel Hazard Estimation

Revista Colombiana de Estadística
This 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, MARÍA DOLORES MARTÍNEZ-MIRANDA, JENS PERCH NIELSEN, JAAP SPREEUW, CARSTEN TANGGAARD, ANDRÉS M. VILLEGAS   +5 more
doaj   +1 more source

An integrative shrinkage estimator for random-effects meta-analysis of rare binary events

Contemporary Clinical Trials Communications, 2018
Meta-analysis has been a powerful tool for inferring the treatment effect between two experimental conditions from multiple studies of rare binary events. Recently, under a random-effects (RE) model, Bhaumik et al.
Lie Li, Ou Bai, Xinlei Wang
doaj   +1 more source

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
doaj   +1 more source

Nonparametric Estimates of Low Bias

Revstat Statistical Journal, 2010
REVSTAT-Statistical Journal, Vol. 10 No.
Christopher S. Withers, Saralees Nadarajah   +1 more
openaire   +3 more sources

Parametric Estimation in Fractional Stochastic Differential Equation

Stats
Fractional Stochastic Differential Equations are becoming more popular in the literature as they can model phenomena in financial data that typical Stochastic Differential Equations models cannot.
Paramahansa Pramanik, Edward L. Boone, Ryad A. Ghanam   +2 more
doaj   +1 more source

Quadripartitioned Neutrosophic Soft Pre - Open And Pre - Closed Sets [PDF]

Neutrosophic Sets and Systems
This paper introduces the development of an almost unbiased estimator for estimating the unknown population median of the primary variable. The proposed estimator leverages neutrosophic auxiliary information and employs simple random sampling without ...
S. Ramesh Kumar, Dr. A. Stanis Arul Mary
doaj   +1 more source

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source