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Sparse semiparametric discriminant analysis

Mai, Qing; Zou, Hui - In: Journal of Multivariate Analysis 135 (2015) C, pp. 175-188

In recent years, a considerable amount of work has been devoted to generalizing linear discriminant analysis to overcome its incompetence for high-dimensional classification (Witten and Tibshirani, 2011, Cai and Liu, 2011, Mai et al., 2012 and Fan et al., 2012). In this paper, we develop...

Persistent link: https://www.econbiz.de/10011189569

A variable selection criterion for linear discriminant rule and its optimality in high dimensional and large sample data

Hyodo, Masashi; Kubokawa, Tatsuya - In: Journal of Multivariate Analysis 123 (2014) C, pp. 364-379

In this paper, we suggest the new variable selection procedure, called MEC, for linear discriminant rule in the high dimensional and large sample setup. MEC is derived as a second-order unbiased estimator of the misclassification error probability of the linear discriminant rule (LDR). It is...

Persistent link: https://www.econbiz.de/10010718981

Asymptotic expansion and estimation of EPMC for linear classification rules in high dimension

Kubokawa, Tatsuya; Hyodo, Masashi; Srivastava, Muni S. - In: Journal of Multivariate Analysis 115 (2013) C, pp. 496-515

The problem of classifying a new observation vector into one of the two known groups distributed as multivariate normal with common covariance matrix is considered. In this paper, we handle the situation that the dimension, p, of the observation vectors is less than the total number, N, of...

Persistent link: https://www.econbiz.de/10010608107

Does modeling lead to more accurate classification?: A study of relative efficiency in linear classification

Lee, Yoonkyung; Wang, Rui - In: Journal of Multivariate Analysis 133 (2015) C, pp. 232-250

experiments under various settings for comparisons of finite-sample performance and robustness to mislabeling and model …

Persistent link: https://www.econbiz.de/10011116232

Inference on the shape of elliptical distributions based on the MCD

Paindaveine, Davy; Van Bever, Germain - In: Journal of Multivariate Analysis 129 (2014) C, pp. 125-144

, that inherit the good robustness properties of the MCD. The main emphasis is on asymptotic results, for point estimation …-Carlo studies illustrate our asymptotic results and assess the robustness of the proposed procedures. …

Persistent link: https://www.econbiz.de/10011041923

Robust empirical likelihood inference for generalized partial linear models with longitudinal data

Qin, Guoyou; Bai, Yang; Zhu, Zhongyi - In: Journal of Multivariate Analysis 105 (2012) 1, pp. 32-44

random vectors to achieve robustness against outliers in both the response and covariates. Simulation studies demonstrate the …

Persistent link: https://www.econbiz.de/10010576502

Robust multivariate association and dimension reduction using density divergences

Iaci, Ross; Sriram, T.N. - In: Journal of Multivariate Analysis 117 (2013) C, pp. 281-295

of the optimal robust association index. Extensive simulation studies are performed to assess the robustness of these …

Persistent link: https://www.econbiz.de/10010665713

Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models

Härdle, Wolfgang Karl; Ritov, Ya’acov; Wang, Weining - In: Journal of Multivariate Analysis 134 (2015) C, pp. 129-145

This study considers the theoretical bootstrap “coupling” techniques for nonparametric robust smoothers and quantile … regression, and we verify the bootstrap improvement. To handle the curse of dimensionality, a variant of “coupling” bootstrap … bootstrap method can be used in many situations such as constructing confidence intervals and bands. We demonstrate the …

Persistent link: https://www.econbiz.de/10011189579

Bootstrap confidence bands and partial linear quantile regression

Song, Song; Ritov, Ya’acov; Härdle, Wolfgang K. - In: Journal of Multivariate Analysis 107 (2012) C, pp. 244-262

In this paper bootstrap confidence bands are constructed for nonparametric quantile estimates of regression functions … bootstrap approximation provides an improvement. The case of multidimensional and discrete regressor variables is dealt with …

Persistent link: https://www.econbiz.de/10011041950

A direct bootstrapping technique and its application to a novel goodness of fit test

Radulovic, Dragan - In: Journal of Multivariate Analysis 107 (2012) C, pp. 181-199

statistics Hn and its bootstrap version Hn∗, without stipulating the existence of weak limits. As one possible application we …

Persistent link: https://www.econbiz.de/10011041981