Discussion of: Treelets--An adaptive multi-scale basis for sparse unordered data (2008)
Bickel, Peter J., Ritov, Ya'acov
Discussion of "Treelets--An adaptive multi-scale basis for sparse unordered data" [arXiv:0707.0481]
Bickel, Peter J., Chen, Chao, Kwon, Jaimyoung, Rice, John, Van Zwet, Erik, Varaiya, Pravin
A traffic performance measurement system, PeMS, currently functions as a statewide repository for traffic data gathered by thousands of automatic sensors. It has integrated data collection,...
Discussion: The Dantzig selector: Statistical estimation when $p$ is much larger than $n$ (2008)
Discussion of "The Dantzig selector: Statistical estimation when $p$ is much larger than $n$" [math/0506081]
Regularized estimation of large covariance matrices (2008)
Bickel, Peter J., Levina, Elizaveta
This paper considers estimating a covariance matrix of $p$ variables from $n$ observations by either banding or tapering the sample covariance matrix, or estimating a banded version of the inverse of...
Sparse permutation invariant covariance estimation (2008)
Rothman, Adam J., Bickel, Peter J., Levina, Elizaveta, Zhu, Ji
The paper proposes a method for constructing a sparse estimator for the inverse covariance (concentration) matrix in high-dimensional settings. The estimator uses a penalized normal likelihood...
Hierarchical selection of variables in sparse high-dimensional regression (2008)
Bickel, Peter J., Ritov, Ya'acov, Tsybakov, Alexander B.
We study a regression model with a huge number of interacting variables. We consider a specific approximation of the regression function under two ssumptions: (i) there exists a sparse representation...
Simultaneous analysis of Lasso and Dantzig selector (2008)
Bickel, Peter J., Ritov, Ya'acov, Tsybakov, Alexandre B.
We exhibit an approximate equivalence between the Lasso estimator and Dantzig selector. For both methods we derive parallel oracle inequalities for the prediction risk in the general nonparametric...
Efficient independent component analysis (2007)
Independent component analysis (ICA) has been widely used for blind source separation in many fields such as brain imaging analysis, signal processing and telecommunication. Many statistical...
Texture synthesis and nonparametric resampling of random fields (2006)
Levina, Elizaveta, Bickel, Peter J.
This paper introduces a nonparametric algorithm for bootstrapping a stationary random field and proves certain consistency properties of the algorithm for the case of mixing random fields. The...
Texture synthesis and nonparametric resampling of random fields (2006)
Levina, Elizaveta, Bickel, Peter J.
This paper introduces a nonparametric algorithm for bootstrapping a stationary random field and proves certain consistency properties of the algorithm for the case of mixing random fields. The...
Tailor-made tests for goodness of fit to semiparametric hypotheses (2006)
Bickel, Peter J., Ritov, Ya'acov, Stoker, Thomas M.
We introduce a new framework for constructing tests of general semiparametric hypotheses which have nontrivial power on the $n^{-1/2}$ scale in every direction, and can be tailored to put substantial...
Tailor-made tests for goodness of fit to semiparametric hypotheses (2006)
Bickel, Peter J., Ritov, Ya’acov, Stoker, Thomas M.
We introduce a new framework for constructing tests of general semiparametric hypotheses which have nontrivial power on the n−1/2 scale in every direction, and can be tailored to put substantial...
Regularization in statistics (2006)
Bickel, Peter J, Li, Bo, Tsybakov, Alexandre B., Yu, Bin, Valdés, Teófilo, ...
This paper is a selective review of the regularization methods scattered in statistics literature. We introduce a general conceptual approach to regularization and fit most existing methods into it....
Estimating Motifs Under Order Restrictions (2005)
Van Zwet, Erik W, Kechris, Katherina J, Bickel, Peter J, Eisen , Michael B.
Transcription factors and many other DNA-binding proteins recognize more than one specific sequence. Among sequences recognized by a given DNA-binding protein, different positions exhibit varying...
Estimating Motifs Under Order Restrictions (2005)
Van Zwet, Erik W, Kechris, Katherina J, Bickel, Peter J, Eisen , Michael B.
Transcription factors and many other DNA-binding proteins recognize more than one specific sequence. Among sequences recognized by a given DNA-binding protein, different positions exhibit varying...
Estimating Motifs Under Order Restrictions (2005)
Van Zwet, Erik W, Kechris, Katherina J, Bickel, Peter J, Eisen , Michael B.
Transcription factors and many other DNA-binding proteins recognize more than one specific sequence. Among sequences recognized by a given DNA-binding protein, different positions exhibit varying...
Estimating Motifs Under Order Restrictions (2005)
Van Zwet, Erik W, Kechris, Katherina J, Bickel, Peter J, Eisen , Michael B.
Transcription factors and many other DNA-binding proteins recognize more than one specific sequence. Among sequences recognized by a given DNA-binding protein, different positions exhibit varying...
Bickel, Peter J., Levina, Elizaveta
We show that the `naive Bayes' classifier which assumes independent covariates greatly outperforms the Fisher linear discriminant rule under broad conditions when the number of variables grows faster...
Detecting DNA regulatory motifs by incorporating positional trends in information content (2004)
Kechris, Katherina J, Van Zwet, Erik, Bickel, Peter J, Eisen, Michael B
Abstract On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery...
Detecting DNA regulatory motifs by incorporating positional trends in information content (2004)
Kechris, Katherina J., Van Zwet, Erik, Bickel, Peter J., Eisen, Michael B.
On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods....
Discussions of boosting papers, and rejoinders (2004)
Bartlett, Peter L., Bickel, Peter J., Bühlmann, Peter, Freund, Yoav, Friedman, Jerome, Hastie, Trevor, ...
Discussions of: "Process consistency for AdaBoost" [Ann. Statist. 32 (2004), no. 1, 13-29] by W. Jiang; "On the Bayes-risk consistency of regularized boosting methods" [ibid., 30-55] by G. Lugosi and...
Nonparametric estimators which can be "plugged-in" (2003)
Bickel, Peter J., Ritov, Ya'acov
We consider nonparametric estimation of an object such as a probability density or a regression function. Can such an estimator achieve the ratewise minimax rate of convergence on suitable function...
The limiting behavior of sums of functions of nearest neighbor distances is studied for an m dimensional sample. A central limit theorem and moment bounds for such sums, and an invariance principle...
Computational Speed Up of Atmospheric Chemistry Models with Hoeffding Formula Approximators (2000)
Peter J. Bickel, Timothy C. Haas
Introduction Several approximators based on Hoeding formulas are described and evaluated for the purpose of reducing the computational expense of three dimensional atmospheric chemistry models....
A New Methodology for Evaluating Incident Detection Algorithms (2000)
Petty, Karl, Bickel, Peter J., Kwon, Jaimyoung, Ostland, Michael, Rice, John
We present a novel, off-line approach for evaluating incident detection algorithms. Previous evaluations have focused on determining the detection rate versus false alarm rate curve -- a process...
A New Methodology for Evaluating Incident Detection Algorithms (1999)
Karl F. Petty, Peter J. Bickel, Jaimyoung Kwon, Michael Ostl, John Rice
We present a novel, off-line approach for evaluating incident detection algorithms. Previous evaluations have focused on determining the detection rate versus false alarm rate curve --- a process...
Bickel, Peter J., Bühlmann, Peter
We study a bootstrap method for stationary real-valued time series, which is based on the sieve of autoregressive processes. Given a sample satisfies a new type of mixing condition. This implies that...
The m Out of n Bootstrap and Goodness of Fit Tests with Doubly Censored Data (1999)
. This paper considers the use of the m out of n bootstrap (Bickel, Goetze, and van Zwet, 1994) in setting critical values for Cram'ervon Mises goodness of fit tests with doubly censored data. We...
TESTS FOR MONOTONE FAILURE RATE BASED ON NORMALIZED SPACINGS. (1998)
Bickel,Peter J., Doksum,Kjell A.
Let X sub (1) < ... < X sub (n) be the order statistics of a random sample from a population with density f and distribution function F such that F(0) = 0. Let q(t) = f(t)/(1 - F(t)) be the failure...
Asymptotic Theory of Selection Procedures and Optimality of Gupta's Rules, (1998)
Bickel,Peter J., Yahav,Joseph A.
Sponsored in part by Grant NSF-MCS79-03716.
Bickel,Peter J., Herzberg,Agnes M., Schilling,Mark F.
See also AD-A101 968.
Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models (1998)
Bickel, Peter J., Ritov, Ya’acov, Rydén, Tobias
Hidden Markov models (HMMs) have during the last decade become a widespread tool for modeling sequences of dependent random variables. Inference for such models is usually based on the...
On a semiparametric survival model with flexible covariate effect (1998)
Nielsen, Jens P., Linton, Oliver, Bickel, Peter J.
A semiparametric hazard model with parametrized time but general covariate dependency is formulated and analyzed inside the framework of counting process theory. A profile likelihood principle is...
On a semiparametric survival model with flexible covariate effect (1998)
Nielsen, Jens P., Linton, Oliver B., Bickel, Peter J.
A semiparametric hazard model with parametrized time but general covariate dependency is formulated and analyzed inside the framework of counting process theory. A profile likelihood principle is...
On a semiparametric survival model with flexible covariate effect (1998)
Nielsen, Jens P., Linton, Oliver B., Bickel, Peter J.
A semiparametric hazard model with parametrized time but general covariate dependency is formulated and analyzed inside the framework of counting process theory. A profile likelihood principle is...
Singly and Doubly Censored Current Status Data: Estimation, Asymptotics and Regression (1994)
Van Der Laan, Mark J., Bickel, Peter J., Jewell, Nicholas P.
In biostatistical applications interest is often focused on the estimation of the distribution of time between two consecutive events. If the initial event time is observed and the subsequent event...
Singly and Doubly Censored Current Status Data: Estimation, Asymptotics and Regression (1994)
Van Der Laan, Mark J., Bickel, Peter J., Jewell, Nicholas P.
In biostatistical applications interest is often focused on the estimation of the distribution of time between two consecutive events. If the initial event time is observed and the subsequent event...
Singly and Doubly Censored Current Status Data: Estimation, Asymptotics and Regression (1994)
Van Der Laan, Mark J., Bickel, Peter J., Jewell, Nicholas P.
In biostatistical applications interest is often focused on the estimation of the distribution of time between two consecutive events. If the initial event time is observed and the subsequent event...
Bickel, Peter J, El Karoui, Nicole, Hennequin, Paul Louis
Incluye bibliografía
Asymptotically nonparametric statistical inference in the multivariate case. (1963)
Thesis (Ph. D. in Statistics)--Univ. of California, Sept. 1963.
Finding important sites in protein sequences
Bickel, Peter J., Kechris, Katherina J., Spector, Philip C., Wedemayer, Gary J., Glazer, Alexander N.
By using sequence information from an aligned protein family, a procedure is exhibited for finding sites that may be functionally or structurally critical to the protein. Features based on sequence...
Detecting DNA regulatory motifs by incorporating positional trends in information content
Kechris, Katherina J, Van Zwet, Erik, Bickel, Peter J, Eisen, Michael B
On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, a simple extension to the model-based motif discovery method is proposed....
Kechris, Katherina J., Lin, Jason C., Bickel, Peter J., Glazer, Alexander N.
Lateral gene transfer (LGT) is now accepted as an important factor in the evolution of prokaryotes. Establishment of the occurrence of LGT is typically attempted by a variety of methods that includes...
Finding important sites in protein sequences
Bickel, Peter J., Kechris, Katherina J., Spector, Philip C., Wedemayer, Gary J., Glazer, Alexander N.
By using sequence information from an aligned protein family, a procedure is exhibited for finding sites that may be functionally or structurally critical to the protein. Features based on sequence...
Detecting DNA regulatory motifs by incorporating positional trends in information content
Kechris, Katherina J, Van Zwet, Erik, Bickel, Peter J, Eisen, Michael B
On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, a simple extension to the model-based motif discovery method is proposed....
Goodness-of-fit tests for regression using kernel methods
Aït-Sahalia, Yacine., Bickel, Peter J., Stoker, Thomas M.
HD28 .M414 no.3747-94,
Testing and the method of sieves
Bickel, Peter J., Ritov, Ya'Acov., Stoker, Peter J.
HD28 .M414 no.4028-98,