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Asymptotic equivalence for nonparametric generalized linear models
Nonparametric regression Statistical experiment De® - ciency distance Global white noise approximation Exponential family Variance stabilizing transformation
2015/8/25
We establish that a non-Gaussian nonparametric regression model is asymptotically equivalent to a regression model with Gaussian noise. The approximation is in the sense of Le Cam's de®- ciency d...
Di€usion approximation for nonparametric autoregression
Nonparametric experiments de® ciency distance likelihood ratio process stochastic di€ erential equation autoregression di€ usion sampling asymptotic su ciency
2015/8/25
A nonparametric statistical model of small di€usion type is compared with its discretization by a stochastic Euler di€erence scheme. It is shown that the discrete and continuous models are a...
ASYMPTOTIC EQUIVALENCE OF DENSITY ESTIMATION AND GAUSSIAN WHITE NOISE
ASYMPTOTIC EQUIVALENCE DENSITY ESTIMATION GAUSSIAN WHITE NOISE
2015/8/25
Signal recovery in Gaussian white noise with variance tending to zero has served for some time as a representative model for nonparametric curve estimation, having all the essential traits in a pure f...
ON THE ESTIMATION OF A SUPPORT CURVE OF INDETERMINATE SHARPNESS
Convergence rate curve estimation endpoint order statistic regular variation support
2015/8/25
We propose nonparametric methods for estimating the support curve of a bivariate density, when the density decreases at a rate which might vary along the curve. Attention is focussed on cases where th...
Asymptotic Equivalence of Density Estimation and Gaussian White Noise
Asymptotic Equivalence Density Estimation Gaussian White Noise
2015/8/25
Signal recovery in Gaussian white noise with variance tending to zero has served for some time as a representative model for nonparametric curve estimation, having all the essential traits in a pure f...
ADAPTIVE SPLINE ESTIMATES FOR NONPARAMETRIC REGRESSION MODELS
ADAPTIVE SPLINE ESTIMATES NONPARAMETRIC REGRESSION MODELS
2015/8/25
ADAPTIVE SPLINE ESTIMATES FOR NONPARAMETRIC REGRESSION MODELS.
Can Recent Innovations in Harmonic Analysis ‘Explain’ Key Findings in Natural Image Statistics?
Recent Innovations Natural Image Statistics
2015/8/21
Recently, applied mathematicians have been pursuing the goal of sparse coding of
certain mathematical models of images with edges. They have found by mathematical
analysis that, instead of wavelets ...
REGRESSION WITH AN ORDERED CATEGORICAL RESPONSE
Proportional odds Ordered categorical Non-parametric
2015/8/21
A survey on Mselenijoint disease in South Africa involved the scoring ofpelvic X-rays of women to measure osteoporosis. The scores were ordinal by construction and ranged from 0 to 12. It is standard ...
Shrinking Trees
Shrinking Trees
2015/8/21
Tree-based models provide an alternative to linear models for classification and regression data. They are used primarily for exploratory analysis of complex data or as a diagnostic tool following a l...
Asymptotic Minimaxity of False Discovery Rate Thresholding for Sparse Exponential Data
Minimax Decision theory Minimax Bayes estimation
2015/8/21
Control of the False Discovery Rate (FDR) is a recent innovation in multiple hypothesis
testing, allowing the user to limit the fraction of rejected null hypotheses which correspond to
false rejecti...
Discriminant Adaptive Nearest Neighbor Classification
lassification nearest neighbors linear discriminant an,alysis,curse of dimensionality
2015/8/21
earest neighbor classification expects the class conditional probabilities to be locally constant,and suffers from bias in high dimensions. We propose a locally adaptive form of nearest neighbor class...
Metricsand Models forHandwritten CharacterRecognition
Nearest Neighbor Classification invariance
2015/8/21
Metricsand Models forHandwritten CharacterRecognition.
Statistical Mo dels for Image Sequences.
Imputing Missing Data for Gene Expression Arrays
Imputing Missing Data Gene Expression Arrays
2015/8/21
Here we describe three different methods for imputation.The first is based on a reduced rank SVD of the expression matrix, the second is based on K-nearest neighbor averaging, and the third is based o...