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Displaying records 51 to 60 of 112 records.
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51. Model Selection for Good Estimation and Prediction Over a User-Speci ed Covariate Distribution for Linear Models Under the Frequentist Paradigm
Topic: Statistics
Published: 10/26/2011
Author: Adam L Pintar
Abstract: Model selection is an important part of estimation and prediction for linear models with multiple explanatory variables (covariates). A variety of approaches exist that focus on estimation of model parameters or the t of the model where data have be ...

Series: Journal of Research (NIST JRES)
Report Number: 116-5
Topic: Statistics
Published: 10/5/2011
Authors: Kevin L Mills, James J Filliben
Abstract: Experimenters characterize the behavior of simulation models for data communications networks by measuring multiple responses under selected parameter combinations. The resulting multivariate data may include redundant responses reflecting aspects of ...

53. A Bayesian Statistical Model for Hybrid Metrology to Improve Measurement Accuracy
Topic: Statistics
Published: 7/31/2011
Authors: Richard M Silver, Nien F Zhang, Bryan M Barnes, Jing Qin, Hui H. Zhou, Ronald G Dixson
Abstract: We present a method to combine measurements from different techniques that reduces uncertainties and can improve measurement throughput. The approach directly integrates the measurement analysis of multiple techniques that can include different conf ...

54. Bayesian uncertainty analysis for a regression model versus application of GUM Supplement 1 to the least-squares estimate
Topic: Statistics
Published: 5/5/2011
Authors: Blaza Toman, Clemens Elster
Abstract: Application of least-squares as, for instance, in curve fitting is an important tool of data analysis in metrology. It is tempting to employ the supplement 1 to the GUM (GUM-S1) to evaluate the uncertainty associated with the resulting parameter esti ...

55. Estimating Common Parameters in Heterogeneous Random Effects Models
Topic: Statistics
Published: 4/13/2011
Author: Andrew L Rukhin
Abstract: A question of fundamental importance for meta-analysis of heterogeneous data studies is how to form a best consensus estimator of common parameters, and what uncertainty to attach to the estimate. This issue is addressed for a class of unbalanced lin ...

56. Maximum Likelihood and Restricted Likelihood Solutions in Multiple-Method Studies
Series: Journal of Research (NIST JRES)
Topic: Statistics
Published: 1/31/2011
Author: Andrew L Rukhin
Abstract: A formulation of the problem of combining data from several sources is discussed in terms of random effects models. The unknown measurement precision is not supposed to be constant among laboratories whose summary results may seem not to conform to ...

57. A chapter ``Statistical Testing of Randomness: New and Old Procedures '' Statistical Engineering Division is a contribution to the book "Randomness: Five Questions"
Topic: Statistics
Published: 1/11/2011
Author: Andrew L Rukhin
Abstract: Several procedures designed to test randomness of binary sequences are reviewed. Necessary modifications to the existing document ``A statistical test suite for the validation of cryptographic random number generators'', Special NIS ...

58. Limit of detection determination for censored samples.
Topic: Statistics
Published: 1/11/2011
Author: Andrew L Rukhin
Abstract: The problem of setting the limit of detection is considered for censored samples and heterogeneous errors. After formal definitions of the critical level and of the method detection limit, we introduce simplified maximum likelihood-type estimators ...

59. Reducing Data Nonconformity in Linear Models
Topic: Statistics
Published: 1/3/2011
Author: Andrew L Rukhin
Abstract: Stein phenomenon Summary Several procedures designed to reduce nonconformity in interlaboratory studies by shrinking data toward a consensus matrix weighted mean are suggested. Some of them are shown to have a smaller quadratic risk than the vector s ...

60. Laplace Random Effects Models for Interlaboratory Studies
Topic: Statistics
Published: 11/25/2010
Authors: Andrew L Rukhin, Antonio M Possolo
Abstract: A model is introduced for measurements obtained in collaborative interlaboratory studies, comprising measurement errors and random laboratory effects that have Laplace distributions, possibly with heterogeneous, laboratory-specific variances. Estima ...

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