Results 61 to 70 of about 5,750 (118)

Deconvolution Estimation in Measurement Error Models: The R Package decon

Journal of Statistical Software, 2011
Data from many scientific areas often come with measurement error. Density or distribution function estimation from contaminated data and nonparametric regression with errors in variables are two important topics in measurement error models.
Xiao-Feng Wang, Bin Wang
doaj  

Strong convergence for weighted sums of (α, β)-mixing random variables and application to simple linear EV regression model

Open Mathematics
In this article, the complete convergence and the Kolmogorov strong law of large numbers for weighted sums of (α,β)\left(\alpha ,\beta )-mixing random variables are presented.
Hu Wenjing, Wang Wei, Wu Yi
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Using community‐reported data to understand how boat speed affects marine wildlife: An example with the Florida manatee

Ecological Solutions and Evidence
Boat collisions are a known and increasing threat to many marine wildlife populations. The Florida manatee Trichechus manatus latirostris is a key example of a species with high boat‐related mortality, whose long‐term viability and population are limited
Bea Combs‐Hintze, Jeffrey A. Hostetler, Charles S. Calleson, Brandon L. Bassett, Cameron H. Ainsworth, Julien Martin   +5 more
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LogitBoost with errors-in-variables

Computational Statistics & Data Analysis, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Joseph Sexton, Petter Laake
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Error checking with pointer variables

Proceedings of the annual conference on - ACM 76, 1976
The use of pointer variables in a programming language often results in a difficult class of errors to detect. Pointers may point to storage that no longer is allocated, or storage may be allocated as one data type and accessed as another. This report describes the implementation of pointers in the PLUM PL/1 compiler such that all error conditions are ...
Marvin V. Zelkowitz, Paul R. McMullin, Keith R. Merkel, Howard J. Larsen   +3 more
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Optimal errors-in-variables filtering

Automatica, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guidorzi R., Diversi R., Soverini U.
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Dynamic errors-in-variables systems with three variables

Automatica, 1987
Errors-in-variables problems are considered for the case of three variables, where the underlying relations among the noise-free variables are linear, and covariance information for the noisy variables is available. The static problem where the variables are complex (which can arise when narrowband filtering is used) is analyzed in detail. Some results
Brian D. O. Anderson, Manfred Deistler
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Errors in Variables

1987
This essay surveys the history and recent developments on economic models with errors in variables. These errors may arise from the use of substantive unobservables, such as permanent income, or from ordinary measurement problems in data collection and processing.
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On the identifiability of errors-in-variables models with white measurement errors

Automatica, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
BOTTEGAL, GIULIO, PICCI, GIORGIO, PINZONI, STEFANO   +2 more
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Error in Variables

2003
AbstractThis chapter analyses the standard regression model with errors in variables. It covers measurement error bias and unobserved heterogeneity bias, instrumental variable estimation with panel data. It presents estimates from Bover and Watson (2000) concerning economies of scale in a firm money demand equation.
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