Results 71 to 80 of about 2,712,723 (299)

A Note on the Efficiency of Least-Squares Estimates

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1968
Summary A linear model is considered in which errors are independent and identically distributed with zero mean. If the error distribution is specified, except possibly for unknown parameters, the asymptotic efficiency of least-squares estimates relative to maximum-likelihood estimates can be found.
Cox, D. R., Hinkley, D. V.
openaire   +2 more sources

Reweighted Least Trimmed Squares: An Alternative to One-Step Estimators [PDF]

A new class of robust regression estimators is proposed that forms an alternative to traditional robust one-step estimators and that achieves the √n rate of convergence irrespective of the initial estimator under a wide range of distributional ...
Cizek, P.
core  

Refinement of amino‐acid conformation vs. difference density maps in time‐resolved serial femtosecond crystallography data analysis

FEBS Open Bio, EarlyView.
The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong, Yuhei Hosokawa, Lars Oliver Essen, Manuel Maestre‐Reyna   +3 more
wiley   +1 more source

On the equivalence between Total Least Squares and Maximum Likelihood PCA

, 2005
The maximum likelihood PCA (MLPCA) method has been devised in chemometrics as a generalization of the well-known PCA method in order to derive consistent estimators in the presence of errors with known error distribution.
Wentzell, P., Van Huffel, S., Schuermans, M., Markovsky, I.   +3 more
core   +1 more source

Employment Bootstrapping Approach to Finding New Ratio Estimators in Simple Random Sampling [PDF]

المجلة العراقية للعلوم الاحصائية, 2009
This research boils down to find new ratio estimators instead of estimators of (Kadilar and Cingi ;2004) by replacing the regression parameter of the final estimators, which is estimated by ordinary least squares, with new parameter estimated by ...
doaj   +1 more source

H∞ Bounds for Least-Squares Estimators

, 1997
In this paper we obtain upper and lower bounds for the H 1 norm of the Kalman filter and RLS algorithm, with respect to prediction and filtered errors. These bounds can be used to study the robustness properties of such estimators.
Thomas Kailath, Bounds For Least-squares Estimators, Babak Hassibi   +2 more
core  

Characterization of the asymptotic distribution of semiparametric M-estimators [PDF]

, 2010
This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.
Sokbae Lee, Ichimura, H, Ichimura, Hidehiko, Lee, S, Hidehiko Ichimura, Lee, Sokbae   +5 more
core   +1 more source

Sudden anaerobization in Amphibacillus xylanus increases intracellular labile ferrous iron and inhibits cell growth

FEBS Open Bio, EarlyView.
Abruptly changing from aerobic to anaerobic conditions (sudden anaerobization) induced growth inhibition and a significant increase in intracellular labile ferrous iron in the aerotolerant anaerobe Amphibacillus xylanus. We found that free flavins mediate efficient electron transfer from NADH to ferric iron under anaerobic conditions, suggesting that ...
Shinya Kimata, Yoichi Sakai, Keisuke Tanaka, Etsuro Yoshimura, Ken Kitano, Morio Ishikawa, Tadahiro Nakamoto, Tsutomu Takayama, Hirofumi Inoue, Kaho Nomura, Tomonori Suzuki, Masataka Uchino, Akira Abe, Youichi Niimura   +13 more
wiley   +1 more source

The performance of some new estimated ridge parameter regression model [PDF]

مجلة جامعة الانبار للعلوم الصرفة
In the presence of high correlation between the independent variables in the linear regression model, which is known as the multicollinearity problem, the ordinary least squares estimator produces large variations in the sample. To overcome this problem,
Fatima ALfahdawe, Mustafa Alheety
doaj   +1 more source

Jackknifing Weighted Least Squares Estimators

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1989
SUMMARY In a heteroscedastic linear regression model, the ordinary jackknife estimator of the asymptotic covariance matrix of the weighted least squares estimator is proved to be inconsistent. A modified jackknife procedure is proposed and shown to produce consistent estimators of the asymptotic covariance matrix.
openaire   +2 more sources