Results 1  10
of
3,940,048
Prediction/estimation With Simple Linear Models: Is It Really That Simple?
, 2004
"... Consider the simple normal linear regression model for estimation/prediction at a new design point. When the slope parameter is not obviously nonzero, hypothesis testing and model selection methods can be used for identifying the right model. We compare performance of such methods both theoretically ..."
Abstract

Cited by 12 (1 self)
 Add to MetaCart
Consider the simple normal linear regression model for estimation/prediction at a new design point. When the slope parameter is not obviously nonzero, hypothesis testing and model selection methods can be used for identifying the right model. We compare performance of such methods both
A SIMPLE LINEAR MODEL OF DEMAND PAGING PERFORMANCE by
, 1972
"... © ACM, 1974. This is the author's version of the work, posted by permission of ACM. The definitive version was published in Communications of the ACM 17, 4 (April 1974) pages 181186. ..."
Abstract
 Add to MetaCart
© ACM, 1974. This is the author's version of the work, posted by permission of ACM. The definitive version was published in Communications of the ACM 17, 4 (April 1974) pages 181186.
Consistent Estimation of a Simple Linear Model Under Microaggregation
"... A problem statistical offices are increasingly faced with is guaranteeing confidentiality when releasing microdata sets. One method to provide safe microdata to is to reduce the information content of a data set by means of masking procedures. A widely discussed masking procedure is microaggregatio ..."
Abstract
 Add to MetaCart
is microaggregation, a technique where observations are grouped and replaced with their corresponding group means. However, while reducing the disclosure risk of a data file, microaggregation also affects the results of statistical analyses. The paper deals with the impact of microaggregation on a simple linear model
2005b): ”Statistical Inference in a Simple Linear Model under Microaggregation
 Department of Statistics, University of Munich
"... A problem statistical offices are increasingly faced with is guaranteeing confidentiality when releasing microdata sets. One method to provide safe microdata is to reduce the information content of a data set by means of masking procedures. A widely discussed masking procedure is microaggregation, ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
, a technique where observations are grouped and replaced with their corresponding group means. However, while reducing the disclosure risk of a data file, microaggregation also affects the results of statistical analyses. We focus on the effect of microaggregation on a simple linear model. In a
Statistical Inference in a Simple Linear Model Under Microaggregation
"... A problem statistical offices are increasingly faced with is guaranteeing confidentiality when releasing microdata sets. One method to provide safe microdata is to reduce the information content of a data set by means of masking procedures. A widely discussed masking procedure is microaggregation, ..."
Abstract
 Add to MetaCart
, a technique where observations are grouped and replaced with their corresponding group means. However, while reducing the disclosure risk of a data file, microaggregation also affects the results of statistical analyses. We focus on the effect of microaggregation on a simple linear model. In a
Limma: linear models for microarray data
 Bioinformatics and Computational Biology Solutions using R and Bioconductor
, 2005
"... This free opensource software implements academic research by the authors and coworkers. If you use it, please support the project by citing the appropriate journal articles listed in Section 2.1.Contents ..."
Abstract

Cited by 759 (13 self)
 Add to MetaCart
This free opensource software implements academic research by the authors and coworkers. If you use it, please support the project by citing the appropriate journal articles listed in Section 2.1.Contents
Comparisons of tests for the presence of random walk coefficients in a simple linear model
 Journal of the American Statistical Association
, 1983
"... The locally most powerful test is derived for the hypothesis that the regression coefficients are constant over time against the alternative that they vary according to the random walk process. When the regression equation contains the constant term only, comparisons are made with the tests suggeste ..."
Abstract

Cited by 44 (0 self)
 Add to MetaCart
The locally most powerful test is derived for the hypothesis that the regression coefficients are constant over time against the alternative that they vary according to the random walk process. When the regression equation contains the constant term only, comparisons are made with the tests suggested by LaMotte and McWhorter (1978). These are based on exact powers and on three different types of asymptotic efficiencies including the classical Pitman and Bahadur approaches and the new one due to Gregory (1980). The concept of the Bahadur efficiency is extended to cover also the random slopes. Suggestions are made for choosing the test.
Lambertian Reflectance and Linear Subspaces
, 2000
"... We prove that the set of all reflectance functions (the mapping from surface normals to intensities) produced by Lambertian objects under distant, isotropic lighting lies close to a 9D linear subspace. This implies that, in general, the set of images of a convex Lambertian object obtained under a wi ..."
Abstract

Cited by 514 (20 self)
 Add to MetaCart
wide variety of lighting conditions can be approximated accurately by a lowdimensional linear subspace, explaining prior empirical results. We also provide a simple analytic characterization of this linear space. We obtain these results by representing lighting using spherical harmonics and describing
Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models
 Journal of Business and Economic Statistics
, 2002
"... Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled wi ..."
Abstract

Cited by 684 (17 self)
 Add to MetaCart
Time varying correlations are often estimated with Multivariate Garch models that are linear in squares and cross products of the data. A new class of multivariate models called dynamic conditional correlation (DCC) models is proposed. These have the flexibility of univariate GARCH models coupled
Learning to detect natural image boundaries using local brightness, color, and texture cues
 PAMI
, 2004
"... Abstract—The goal of this work is to accurately detect and localize boundaries in natural scenes using local image measurements. We formulate features that respond to characteristic changes in brightness, color, and texture associated with natural boundaries. In order to combine the information from ..."
Abstract

Cited by 625 (18 self)
 Add to MetaCart
significantly outperforms existing approaches. Our two main results are 1) that cue combination can be performed adequately with a simple linear model and 2) that a proper, explicit treatment of texture is required to detect boundaries in natural images. Index Terms—Texture, supervised learning, cue combination
Results 1  10
of
3,940,048