Some personal information:  

E-mail:  :yaacov.ritov@gmail.com; yaacov.ritov@huji.ac.il;  yritov@umich.edu etc.

See MyBirds  for the group of my livingroom  birds.

הבלוג שלי, עברית בלבד          youtube (Hebrew)          Data Science (Hebrew)

B.Sc. 1973 (The Technion, I.I.T., Electrical Engineering), M.Sc., 1980 (The Technion, I.I.T, Electrical Engineering), Ph.D. 1983 , (Statistics, The Hebrew University of Jerusalem).

The Hebrew University of Jerusalem (Mr. and Mrs. Francis Hock Emeritus Chair in Statistics): Lecturer, 1984; Senior Lecturer, 1989; Associate Professor, 1990; Professor, 1992.  

University of Michigan: Professor, 2015 - .  

More details (i.e., CV).

I have learned a lot in my life. Unfortunately, most of it about technicalities. Here are some details. 

Publications, manuscripts, books, thesis, etc.:

.Ph.D.Thesis:Robust Bayes Procedures (1983, advisers:P.J.Bickel and Y.Yahav). 

M.Heymann and J.Ritov:On a linear pursuit game with an unknown trap.J.of Optimization Theory and Applications 42 (1982),421 445.

Y.Ritov: Robust Bayes decision procedures: gross error on the data distribution. The Annals of Statistics, 13 (1985), 626-637.

M. Haviv and Y. Ritov: An approximation to the stationary distribution of a nearly completely decomposable Markov chain and its error bounds SIAM J. of Algebraic and Discrete Methods 7 (1986), 583-586.

M. Haviv, U. G. Y. Ritov, and Rothblum (1987) : Iterative methods for approximating the sub-dominant modulus of an eigenvalue of a non-negative matrix. Linear Algebra and its Applications 87 (1987), 61-76. A Melkman and

Y. Ritov: Minimax estimation of the mean of a general distribution when the parameter of interest is restricted. The Annals of Statistics, 15 (1987), 432-442.

P. J. Bickel and Y. Ritov: Efficient estimation in the errors in variables models. The Annals of Statistics 15 (1987), 513-540.

Y. Ritov: Asymptotic results in robust quasi - Bayesian estimation. J. of Multivariate Analysis 23 (1987), 290- 302.

Y. Ritov: Tightness of monotone random fields. J. Roy. Statist. Soc.-B (1987) 49 , 331-333.

Z. Gilula, A. M. Krieger, and Y. Ritov: Ordinal association in contingency tables: some interpretive aspects. J. Amr. Statist. Assoc. 83 (1989), 540-545.

M. Haviv and Y. Ritov: The variance of the waiting time in a queuing system with jockeying. Stochastic Models 4 (1988), 162-181.

Y. Ritov and J. A. Wellner: Censoring, martingale, and the Cox model, Contemporary Mathematics (AMS) (1988) Volume 80 on Statistical Inference for Stochastic processes, ed. N.H. Prabhu, pages 191-219.

Y. Ritov: Estimating a signal with noisy parameters. Biometrika 76 (1989), 31-38.

Y. Ritov: Monte Carlo computation of the mean of a function with convex support. Computational Statistics and Data Analysis 7 (1989), 269-277.

D. Assaf and Y. Ritov: A double sequential procedure for detecting a change in distribution. Biometrika 75 (1988), 715-722.

D. Assaf and Y. Ritov: A dynamic sampling procedure for detecting a change in the drift of Brownian motion: a non - Bayesian model. The Annals of statistics 17 (1989), 793-800.

P.J. Bickel and Y. Ritov: Estimating integrated squared density derivatives. Sankhya A-50 (1988), 381-393.

Y. Ritov: Estimation of a linear regression model with censored data. The Annals of Statistics 18 (1990), 303-328.

Y. Ritov and P.J. Bickel: Achieving information bounds in semi and non parametric models. The Annals of statistics 18 , (1990), 925-938.

Y. Ritov: Decision theoretic optimality of the CUSUM procedure. The Annals of statistics 18 (1990), 1464-1469.

Y. Ritov: The convergence of an algorithm for finding the distance between a ball in a subspace and a sum of subspaces. SIAM J. of Numerical Analysis, 27 (1990), 1355-1367.

Y. Ritov: Asymptotic efficient estimation of the change point with unknown distributions. The Annals of Statistics 18 (1990), 1829-1839.

Y. Ritov: Estimating functions in semiparametric models, in Estimating Equations (V.P. Godambe ed.) (1991), pp. 319-336. Oxford University Press.

Z. Gilula and Y. Ritov: Inferential ordinal correspondence analysis: motivation derivation and limitation. International Statistical Review, 58 (1990), 99-108.

P.J. Bickel and Y. Ritov (1990): Comment on Silverman et al.: A smoothed EM approach to indirect estimation problems, with particular reference to sterology and tomography. J. of the Royal Statist. Soc. B 52, 311-312 .

P.J. Bickel, Y. Ritov, and J.A. Wellner: Efficient estimation of a probability measure P with known marginal distributions. The Annals of Statistics 19 (1991) 1316-1346.

P. J. Bickel and Y. Ritov: Large sample theory of estimation in biased sampling regression, model I. The Annals of Statistics, 19 (1991), 797-816.

J. Baron, P.C. Badgio, and Y. Ritov: Departures from optimal stopping in an anagram task. Journal of Mathematical Psychology, 35 , (1991), 41-63.

D. Assaf, M. pollak and Y. Ritov: A new look at warning and action lines of surveillance schemes. J. Amr. Statist. Assoc. 87 (1992), 889-895..

Y. Ritov and Z. Gilula: The order restricted MLE in RC model for order restricted contingency tables: estimation and testing for fit. The Annals of Statistics, 19 ( 1991), 2090-2101.

P.J. Bickel, C.A.G. Klaassen, Y. Ritov, and J.A. Wellner: Efficient and Adaptive Estimation in Semiparametric Models , Johns Hopkins University Press, (1994). 2nd edition, Springer Verlag, 1998.

M. Haviv, Y. Ritov, and U. G. Rothblum: Taylor expansions of eigenvalues of perturbed matrices with applications to spectral radii of non-negative matrices. Linear Algebra and its Application 168 (1992), 159-188.

M. Haviv and Y. Ritov: On series expansions of stochastic matrices. SIAM J. of Matrix analysis, 14 (1993), 670-676.

P.J. Bickel and Y. Ritov: Testing for Goodness of Fit: A New Approach, in Nonparametric Statistics and Related Topics (pp. 51-57), Ed.: A. K. Md. E. Saleh, Elsevier, Amsterdam. (1991)

S. Barasch and Y. Ritov: Pruning FFT frequencies. IEEE transactions on Signal Processing 41 (1993), 1398-1400.

D. Assaf and Y. Ritov: Adaptive sampling for detecting a change point in past. Stochastic Analysis 11 (1992), 237-255.

D. Assaf, M. Pollak, Y. Ritov, and B. Yakir: Detecting a change of a normal mean by dynamic sampling with a probability bound on a false alarm. The Annals of Statistics 21, (1993), 1155-1165.

Y. Ritov and Z. Gilula: Analysis of contingency tables by correspondence models subject to order-constraints. J. Amr. Statist. Assoc. 88 (1993), 1380-1387.

P. J. Bickel and Y. Ritov: Efficient estimation using both direct and indirect observations. Th. of Prob. and Appl. 38 (1994) , 194-213. In Russian, Teorija Verojatnostei i ee Primenenija, 38, (1993), 233-258.

M. Haviv and Y. Ritov: Error bounds for non self-adjoint matrices. Numerische. Mathematik, 67 (1994), 491-450.

P.J. Bickel and Y. Ritov: Estimating linear functionals of a PET image. IEEE Tr. of Medical Imaging, 14 , (1995), 81-87.

M. Fygenson and Y. Ritov: Monotone estimating equations for the censored regression model The Annals of Statistics, 22 (1994) 732-746.

P. J. Bickel and Y. Ritov: "Ibragimov Hasminskii models" Fifth Purdue International Symposium on Decision Theory and Related Topics, (1993), pp 51-60.

P. J. Bickel, and Y. Ritov.: Discussion of papers by Feigelson and Nousek in Statistical Challenges in Modern Astronomy (E. Feigelson and G.J. Babu eds), (1993) Springer, New York.

P. J. Bickel and Y. Ritov: An exponential inequality for U-statistics with applications to testing, Probability in the Engineering and Informational Sciences, 9 (1995), .39-52.

Y. Ritov: PM algorithms for calculating minimum X2 estimators with partial observed tables. Computational Statistics and Data Analysis, 20 (1995), 19-33.

P. J. Bickel and Y. Ritov: LAN for ranks in transformation models. Festschrift for Lucien Le Cam, D. Pollard, E. Torgersen, and G. Yang edts (1997). Springer, New York.

P. J. Bickel and Y. Ritov: Inference in Hidden Markov Models I, Bernoulli, 2 (1996), 199-228.

D. Assaf and Y. Ritov: Dynamic sampling applied to problems in optimal control. J. of Optimization Th. and Appl., 95 (1997), 565-580.

M. Haviv and Y. Ritov: Externalities, Tangible Externalities and Queue Disciplines. Management Science, 44, (1998), 850-858. .

J. M. Robins and Y. Ritov: Toward A Curse of Dimensionality Appropriate (CODA) Asymptotic Theory for Semiparametric Models. Statistics in Medicine, 17 (1997), pp. 285-319.

Karl F. Petty, Peter Bickel, Jiming Jiang, Michael Ostland, John Rice, Ya'acov Ritov, and Frederic Schoenberg: Accurate estimation of travel times from single-loop detectors. Transportation Research: Part A-Policy and practice, 32 (1998), 1-17.

Y. Ritov: Estimating mass and shape of domains in PET imaging. Journal of Nonparametric Statistics, 10 (1999), 47-66.

Peter J. Bickel, Ya'acov Ritov and Tobias Ryden: Asymptotic normality of the maximum-likelihood estimator for general hidden Markov models, The Annals of Statistics, 26 (1998), 1614-1635.

P. J. Bickel and Y. Ritov: Non- and semiparametric statistics: compared and contrasted, J. Stat. Plan. Infer., 91 (2000), 209-228.

E. Greenshtein and Y. Ritov: Sampling from a stationary process and detecting a change in the mean of a stationary distribution. Bernoulli, 6 (2000), 679-697.

H. Pasula, S. Russell, M. Ostland, and Y. Ritov, "Tracking many objects with many sensors." In Proc. IJCAI-99, Stockholm, 1999

P. J. Bickel and Y. Ritov (2003), Non-Parametric Estimators Which Can Be `Plugged-In', The Annals of Statistics , 31, 1033-1053.

M. Haviv, M. and Y. Ritov, Homogeneous Customers Renege from invisible queues at Random Times under deteriorating waiting conditions, Queueing Systems, 38 (2001), 495-508.

P. J. Bickel and Y. Ritov: On profile likelihood. Discussion of S. Murphy and A. van der Vaart "On profile likelihood", J. Amr. Statist. Assoc. 95 (2000), 466-468.

Y. Ritov, Y. Kareev, R. Selten, and A. Shmida: "On the use of sample data to estimate rate of energy gain"

M. Osland, P. J. Bickel, K. Petty, J. Rice, Y, Ritov, and X. Zhang: "An EM/MCMC approach to travel time estimation and origin-destination counts". A PATH report

Bar-Gad, Y. and H. Bergman (2000): "The neuronal refractory period causes a short-term peak in the autocorrelation function". Journal of Neuroscience Methods, 104, 155-163.

Bar-Gad, Y. Ritov, E. Vaadia, and H. Bergman (2001), "Failure in identification of overlapping spikes from multiple neuron recording causes artificial correlations", Journal of Neuroscience Methods 107, 1-13.

Y. Ben Shaul, H. Bergman, Y. Ritov, and M. Ables: "Trial to Trial Variability in Stimulus or Action Causes Apparent Correlation and Synchrony in Neuronal Activity", Journal of Neuroscience Methods, J NEUROSCI METH 111 (2): 99-110 OCT 30 2001.

P. J. Bickel, Y. Ritov, and T. Ryden (2002): Hidden Markov model likelihoods and their derivatives behave like i.i.d. ones. Annales de l'Institut Henri Poincare, ANN I H POINCARE-PR 38 (6): 825-846 2002 (Paper) (Extended version)

Y. Ritov, A. Raz and H. Bergman (2002): Detection of onset of neuronal activity by allowing for heterogeneity in the change points. Journal of Neuroscience Methods 122 25-42.(Paper) (Extended version)

Bar-Gad, Y. Ritov and H. Bergman, The High Frequency Discharge Of Pallidal Neurons Disrupts The Interpretation Of Pallidal Correlation Functions, The Basal Ganglia VII, Advances in behavioral biology, Vol 52, editors: Louise F.B. Nicholson and Richard L.M. Faull, Kluwer Academic/Plenum Publishers, Chapter 5, pp 35-42, 2002.

P. J. Bickel, Y. Ritov, and T. Stoker: Nonparametric testing of an index model. , Rothenberg Festschrift, D. Andrews J. Stock (edts.) Cambridge University Press..

P. J. Bickel, Y. Ritov, and T. Stoker (2006): Tailor-made Tests for Goodness-of-Fit to Semiparametric Hypotheses.Annals of Statistics, 34, 721-741.

G. Mosheiov, D. Oron, Y. Ritov (2005), Minimizing flow-time in a single machine with integer batch sizes. Operation Research Letters, 33, 497-501.

Izhar Bar-Gad, Gali Heimer, Ya'acov Ritov and Hagai Bergman: Functional correlations between neighboring neurons in the primate Globus Pallidus are weak or nonexistent. J NEUROSCI 23 (10): 4012-4016 MAY 15 2003

Y. Ritov (2003). Comments on: A theory of statistical models for Monte Carlo integration, by A. Kong, P. McCullagh, D. Nicolae, Z.Tan and X.-L.MengKong, JRSS-B, 65, 613.

G. Mosheiov, D. Oron, Y. Ritov (2004), Flow-shop scheduling with indentical processing-time jobs. Naval Research, to appear.

P. J. Bickel and Y. Ritov (2003): The Golden Chain, a comment. Ann. Stat. to appear Submitted.

Yoel Haitovsky, Hans, Rudolf Lerche, Ya'acov Ritov (edt.) (2003): Foundations of Statistical Inference. Physica-Verlag, Heidelberg.

Bryan G. Reuben , Ya'acov Ritov, Orit Geller, Melinda A. McFarland, Alan G. Marshall, Chava Lifshitz (2004): Applying a new algorithm for obtaining site specific rate constants for H/D exchange of the gas phase proton-bound arginine dimer; Chemical Physics Letters, 380, 88-94.

Sklan, E.H, Lowenthal, A., Korner, M., Ritov, Y., Rankinen, T., Bouchard, C., Leon, A.S., Rao, D.C., Wilmore, J.H., Skinner, J.S. and Soreq, H. (2004). Acetylcholinesterase/paraoxonase genotype and expression predict anxiety scores in Health, Risk Factors, Exercise Training, and Genetics study. PNAS, 101, 5512-5517.

Greenshtein, E. and Ritov, Y. (2004) ``Persistency in high dimensional linear predictor-selection and the virtue of over-parametrization", Bernoulli, 10, 971--988.

Michal Rivlin-Etzion, Ya'acov Ritov, Gali Heimer, Hagai Bergman, Izhar Bar-Gad (2005) ``Local shuffling of spike trains boosts the accuracy of spike train spectral analysis", Journal of Neurophysiology, 95, 3245-3256. .

P. J. Bickel, Y. Ritov, and A. Zakai (2005): ``Some theory for generalized boosting algorithms" Journal of Machine Learning Research, 7, 705--732.

Y. Ritov (2005): ``A deterministic forecaster can be universally calibrated", .

Saul Lach, Ya'acov Ritov, and Avi Simhon (2006): LONGEVITY ACROSS GENERATIONS, Maurice Falk Institute for Economic Research in Israel, Hebrew University, Discussion Paper No. 06.01, Jerusalem 2006, 21 pages

Jon A.Wellner,Chris A.J.Klaassen,Ya'acov Ritov (2006): Semiparametric Models:a Review of Progress since BKRW (1993)., .In Frontier of Statistics, J. Fan and H. L Koul (edts.) pp. 25-44.

Kjell Doksum and Ya'acov Ritov (2006): Our steps on the Bickel way. In Frontier of Statistics, J. Fan and H. L Koul (edts.) pp. 1-24.

Eitan Greenshtein, Junyong Park, Ya'acov Ritov (2008): Estimating the mean of high valued observations in high dimensions.., JSTP, accepted..

Thomas Trigano, Uri Israeles, and Ya'acov Ritov: Semiparametric shift estimation for alignment of ECG data. EUSIPCO 2008.

Yair Goldberg and Ya'acov Ritov (2009).   Procrustes for Manifold Embedding: Quality of Embedding measure and embedding algorithms. Machine Learning. 77,  1-25.

Y. Rabinowicz, I. Roman, and Y. Ritov (2007): "ADVANCED METHODOLOGY FOR ASSESSING DISTRIBUTION CHARACTARISTICS OF PARIS EQUATION COEFFICIENTS  TO IMPROVE FATIGUE LIFE PREDICTION"  Fatigue and Fracture ofEngineering Materials and Structures.  31, 262--269

Alon Zakai and Ya'acov Ritov (2008):  How Local Should a Learning Method Be? COLT 2008, Accepted.

Ya'acov Ritov (2007): Comments following Candes and Tao: The Dantzig selector:statistical estimation when $p$ is much larger than $n$ NNALS OF STATISTICS   Volume: 35   Issue: 6   Pages: 2370-2372

Ya'acov Riotv and Wolfgang K. Haerdle (2007): Investors preference: Estimating and demixing of the weight function in semiparametric models for biased samples. SFB 649 Discussion Paper 2007-024, Humboldt University.  Statisica Sinica  Accepted

Alon Zakai and Ya'acov Ritov (2007): Localized Support Vector Machine for Text Categorization on Changing Datasets.

Yair Goldberg, Alon Zakai, Dan Kushnir, and Ya'acov Ritov (2008): Manifold learning:: the price of normalization? JMLR 9(Aug):1909--1939, 2008. Link: http://www.jmlr.org/papers/volume9/goldberg08a/goldberg08a.pdf

Daniel Gill, Ya'acov Ritov, and Gideon Dror (2007): Is Pinocchio's Nose Long or His Head Small? Learning Shape Distances for Classification. To appear in the proceeding of the 3rd, pringer-Verlag in the Lecture Notes in Computer Science (LNCS) series,

Peter J.  Bickel, Ya'acov Ritov, and Alexandre Tsybakov (2009). Simultaneous analysis of Lasso and Dantzig selector, Annals of Statistics, 37, 1705-1732.

Peter J.  Bickel, Ya'acov Ritov, and Alexandre Tsybakov. Hierarchical selection of variables in sparse high-dimensional regression. IMS Collections, Borrowing Strength: Theory Powering Applications---A Festschrift for Lawrence D. Brown 6. 56-69

Peter J.  Bickel, Ya'acov Ritov (2008) Response to Mease and Wyner,   Evidence Contrary to the Statistical View of Boosting,  And Yet It Overfits. Journal of Machine Learning  Research 9 (2008) 181-186.

Michel BRONIATOWSKI, Alexandre DEPIRE and Ya'acov RITOV (2008). Bivariate Cox Models, Mathematical Methods in Survival Analysis, Reliability and Quality of Life, Edited by C. Huber N. Limnios M. Mesbah and M. Nikulin. Wiley.

Peter J. Bickel and Ya'acov Ritov (2008) Discussion of Treelets--An Adaptive Multi-Scale Basis for Sparse Unordered Data. The Annals of Applied Statistics,. 2. 474--477.

R. Douc, E. Moulines, Y. Ritov (2009)  Forgetting of the initial condition for the filter in general state-space hidden Markov chain: a coupling approach  ELECTRONIC JOURNAL OF PROBABILITY   14   Pages: 27-49

E. Greenshtein and Y. Ritov (2009). Asymptotic efficiency of simple  decisions for the compound decision problem,  Optimality: The Third Erich L. Lehmann Symposium  IMS Lecture Notes, Monograph Series Vol. 57 (2009) 266-275. 

Adam Zaidel, Hagai Bergman, Ya'acov Ritov, and Zvi Israel (2010). Levodopa and subthalamic deep brain stimulation responses are not congruent. Movement Disorder 25 ,2379-2386

U. Isserles, Y. Ritov and T. Trigano (2011):  Semipasrametric curve alignment and shift density estimation for biological data,   IEEE Transactions on Signal Processing 59 , 1970-1984 

Y. Goldberg and Y. Ritov (2008): LLE with low dimensional neighborhood. 4th International Symposium on Visual Computing   (ISVC08).  To appear.   Code .

A. Zakai and Y. Ritov (2009)  Consistency and Localizability   JMLR 10, 827--856.

Elias, S, Ritov, Y. and Bergman, H. (2008) Balance of increases and decreases in firing rate of the spontaneous activity of basal ganglia high-frequency discharge neurons. Journal of Neurophysiology, 3086-3104.

Y. Goldberg and Y. Ritov (2009): LLE with low dimensional neighborhood. Submitted. Short version appears in proceedings of the 4th International Symposium on Visual Computing   (ISVC08).   Code & Datasets

Micha Mandel and Ya'acov Ritov (2009). The accelerated failure time model under biased sampling. Biometrics,  s66 , 1306--1308.

Ya'acov Ritov (2009). A random walk with drift:  Interview with Peter J. Bickel. Statistical Science26 , 150-159.s.

Natalia Bochkina and Ya'acov Ritov (2009). Sparse Empirical Bayes Analysis (SEBA). 

Natalia Bochkina and Ya'acov Ritov (2011) Bayesian Perspectives  on Sparse Empirical Bayes Analysis (SEBA). In Inverse Problems and High-Dimensional Estimation Inverse Problems and High-Dimensional Estimation', Alquier, Pierre; Gautier, Eric; Stoltz, Gilles (Eds.),Lecture Notes in Statistics, Vol. 203.

P. Chigansky and Y. Ritov (2009). A     On the Viterbi process with continuous state space. Bernoulli 17 , 609-627.

Y Ritov (2010) On the trasductive arguments in statistics. s

Hila Zadka; Ya'acov Ritov; Hagai Bergman,  Eli Vakil,  (2010), Soft-max model reveals changes in the exploration-exploitation balance during probabilistic classification tasks.

Brown, L., Greenshtein, E. and Ritov Y. (2013). The Poisson Compound Decision Problem Revisited.  Journal Of The American Statistical Association  108, 741-749 ..

M. Levy and Y. Ritov (2010): Mean-variance efficient portfolios with many assets: 50% short.  Quantitative Finance11, 1461-1471.

Yair Goldberg and Ya'acov Ritov (2010). Theoretical analysis of LLE based on its weighting step. (Proofs) Journal of Csomputational and Graphical Statistics, 21 , 380-393.

Rea Mitelman, Boris Rosin, Hila Zadka, Maya Slovik, Gali Heimer, Ya'acov Ritov, Hagai Bergman, Shlomo Elias (2011). Neighboring pallidal neurons do not exhibit more synchronous oscillations than remote ones in the MPTP primate model of Parkinson's disease. 30  Frontiers in Systems Neuroscience.

Song Song, Ya'acov Ritov,  Wolfgang Karl Haerdle  (2012). Bootstrap confidence bands and partial linear quantile regression. SFB 649 Discussion Paper 2010-002. JOURNAL OF MULTIVARIATE ANALYSIS 107 ,244-262 .

Noam Cohen, Eitan Greenshtein and Ya'acov Ritov (2013).. Empirical Bayes in the presence of explanatory variables. Statistica Sinica. Vol. 23, No. 1, 333-357.

Jianqing Fan, Ya'acov Ritov, C.F. Jeff Wu (Editors, 2013). Selected Works of Peter J. Bickel Springer, New York,

Ritov, Y. (2013). Introduction to four papers by Peter Bickel. In "Selected Works of Peter J. Bickel", Editors: Jianqing Fan, Ya’acov Ritov, C. F. Jeff Wu.

Felix Abramovich; Ya'acov Ritov (2013).  Statistical Theory: A Concise Introduction. Chapman & Hall/CRC Texts in Statistical Science .  Review

Shenhar-Tsarfaty S, Waiskopf N, Ofek K, Shopin L, Usher S, Berliner S, Shapira I, Bornstein NM, Ritov Y, Soreq H, Ben Assayag E. (2013). Atherosclerosis and arteriosclerosis parameters in stroke patients associate with paraoxonase polymorphism and esterase activities. Eur J Neurol. 20, 891-8.

Y. Sepulcre, T. Trigano, Y. Ritov (2013).  "Sparse regression algorithm for activity estimation in Gamma spectrometry”. IEEE Transactions on Signal Processing, 61, 4347--4359

Ya'acov Ritov and Gershon Saar (2013). Remarks on Buehlmann, Ruetimann van de Geer and Zhang: Correlated variables in regression: clustering and sparse estimation. Journal Of Statistical Planning And Inference,   143,   1863-1865.

Daniel Nevo and Ya'acov Ritov (2013). "Around the goal: Examining the effect of the first goal on the second goal in soccer using survival analysis methods", Journal of Quantitative Analysis of Sports . 9 165-177,

Wolfgang Haerdle, Ya'acov Ritov, and Weining Wang  (2014) "Tie the straps: uniform bootstrap confidence bands for bounded influence curve estimators."  Journal of Multivariate Analysis, Accepted.

Song Song, Wolfgang K. Haerdle, Ya'acov Ritov (2014). Generalized Dynamic Semiparametric Factor Models for High Dimensional Nonstationary Time Series.  Econometrics Journal 17, pp. 1-32.

Yair Goldberg., Ya'acov Ritov. and Avishai  Mandelbaum (2014) Predicting the Continuation of a Function with Applications to Call Center Data. Journal of Statistical Planning and Inference, 147, 53—65.    Data and programs

Y. Ritov, P. J. Bickel, A. Gamst, B. J. K. Kleijn (2014), The Bayesian Analysis of Complex, High-Dimensional Models:  Can it be CODA? Statistical Science.

Sara van de Geer, Peter Buehlmann and Ya’acov Ritov (2014). On asymptotically optimal confidence regions and tests for high-dimensional models.  Annals of Statistics.

Malka Gorfine, Yair Goldberg, and Ya'acov Ritov (2016). A Quantile Regression Model for Failure Time Data with Time Dependent Covariates,  Biostatistics, to appear.

Eitan Greenstein, Ariel Mansura,  and Ya'acov Ritov (2014).  Empirical Bayes improvement of Kalman filter estimators.

Shani Shenhar-Tsarfaty,  Nadav Yayon,Nir Waiskopf,Itzhak Shapira, Sharon Toker, David Zaltser, Shlomo Berliner, Ya`acov Ritov, Hermona Soreq (2014). Fear and C-reactive protein co-synergize annual pulse increases in healthy adults. PNAS, to appear.

Edward Ionides, Alexander Giessing, Yaacov Ritov, and Scott E. Page (2016). Response to the ASA's statement on p-values: context, process, and purpose. The American Statistician. 71,   88-89.

Daniel Nevo and Ya'acov Ritov (2015). Minimal class of models for high-dimensional data.

Eitan Greenstein, Ariel Mansura,  and Ya'acov Ritov (2014).  Empirical Bayes improvement of Kalman filter estimators.

Malka Gorfine, Yair Goldberg, and Ya'acov Ritov (2016). A Quantile Regression Model for Failure Time Data with Time Dependent Covariates.Biostatistics, to appear.

Nevo, D., and Ritov, Y. A. (2017). Identifying a Minimal Class of Models for High--dimensional Data. Journal of Machine Learning Research, 18(24), 1-29. 

Jonathan Sidi, Ya'acov Ritov, and Lyle Ungar (2015). Regularization and Classification of Linear Mixed Models via the Elastic Net Penalty with Application to the Good Judgment Project.  

Keren Weinshall Margel, Udi Sommer, and Ya'acov Ritov (2015). A Micro-Macro Gauge of ideological Effects on Judicial Decision Making in High Courts: The Dynamic Comparative Attitudinal Measure and the Ideological Ideal Point Estimate.  Regulation & Governance, to appear.

Ya'acov Ritov (2015). Bayesian and robustness analyses of ¹⁴C data with application to Tel Rehov.

Shenhar-Tsarfaty, Shani; Shapira, Itzhak; Toker, Sharon; Rogowski, Ori; Berliner, Shlomo; Ritov, Yaacov; Soreq, Hermona (2016). Weakened Cholinergic Blockade of Inflammation Associates with Diabetes-Related Depression. Molecular Medicine. To appear.

T. Trigano, Y. Sepulcre,  Y. Ritov (2017). "Sparse Reconstruction Algorithm for Nonhomogeneous Counting Rate Estimation" IEEE Transactions on Signal Processing.

J. D. Rosenblatt, Y. Ritov, and J.J. Goeman (2019).  Discussion of Sesia et al. and the Knockoff Framework. Biometrika 106, pp.  29-–33.

Zvi Gilula, Robert McCulloch, Ya'acov Ritov, and Oleg Urminsky(2018). A Study  into Mechanisms of Attitudinal Scale Conversion: A  Randomized Stochastic Ordering Approach. Quantitative Marketing and Economics

Nhat Ho, Xuanlong Nguyen, Ya'acov Ritov (2018) Robust Estimation of Mixing Measures in Finite Mixture Models. Bernoulli.

Eitan Greenstein, Ariel Mansura,  and Ya'acov Ritov (2019).  Empirical Bayes improvement of Kalman filter estimators.  Bernoulli.

Eitan Greenshtein and Ya'acov Ritov (2019). Empirical Bayes, Compound Decisions and Exchangeability. Statistical Science

Ya'acov Ritov, Yuekai Sun, Ruofei Zhao (2019): On conditional parity as a notion of non-discrimination in machine learning    

Eitan Greenshtein, Ya'acov Ritov (2019): Applications of Generalized Maximum Likelihood Estimators to stratified sampling and post-stratification with many unobserved strata

Hamid Eftekhari, Moulinath Banerjee, Ya'acov Ritov (2019): Inference In General Single-Index Models Under High-dimensional Symmetric Designs. JMLR, accepted.

Hamid Eftekhari, Moulinath Banerjee, Ya'acov Ritov (2019):  Design of c-Optimal Experiments for High dimensional Linear Models. Bernoulli Journal

Michael Law, Ya'acov Ritov (2019): Estimating the Random Effect in Big Data Mixed Models. JASA, to be published.

Debarghya Mukherjee, Moulinath Banerjee, Ya'acov Ritov (2021): "Optimal Linear Discriminators For The Discrete Choice Model In Growing Dimensions" Annals of Statistics  

Michael Law, Ya'acov Ritov (2019): Inference Without Compatibility: Using Exponential Weighting for Inference on a Parameter of a Linear Model. Bernoulli, accepted

Jonathan Yefenof, Yair Goldberg, Jennifer Wiler, Avishai Mandelbaum, Ya'acov Ritov (2019): Self-reporting and screening: Data with current-status and censored observations

Ya'acov Ritov, Yuekai Sun, Ruofei Zhao (2019): On conditional parity as a notion of non-discrimination in machine learning

Ning Ning, Edward Ionides, Ya'acov Ritov (2021). Scalable Monte Carlo Inference and Rescaled Local Asymptotic Normality, Bernoulli, accepted. 

R. Wilf Miron, I. Novikov, A. Ziv, A. Mendelbaum, Y. Ritov, O. Luxenburg (2020). A novel methodology to measure waiting times for community-based specialist care in a public healthcare system. \emph{Health Policy.}

Hamid Eftekhari, Debarghya Mukherjee, Moulinath Banerjee, Ya'acov Ritov (2020). Markovian And Non-Markovian Processes with Active Decision Making Strategies For Addressing The COVID-19 Pandemic.

Brian McNair, Eric Margolin, Michael Law, Ya'acov Ritov (2020). The Hot Hand and Its Effect on the NBA

Debarghya Mukherjee, Moulinath Banerjee, Ya'acov Ritov (2020). Asymptotic normality of a linear threshold estimator in fixed dimension with near-optimal rate.

Debarghya Mukherjee, Moulinath Banerjee and Ya'acov Ritov (2021). Regression discontinuity design: estimating the treatment effect with standard parametric rate. 

  Debarghya Mukherjee, Moulinath Banerjee and Ya'acov Ritov (2021).``On robust learning in the canonical change point problem under heavy tailed errors in finite and growing dimensions"", Electronic Journal of Statistics.

J. Yefenof, Y. Goldberg, and Y. Ritov (2021). "Confidence Intervals for the Test Error in a General Kernel Machine Classification" 

.

Students:

Current:  

Michael Law

Hamid  Eftekhari

Debarghya  Mukherjee

Past:

 Saar Gershuni

Jonathan Yefe-Nof

Jonathan Sidi

Nhat Ho

Ariel Mansura

Thomas Trigano               

Guy Leshem

Alon Zakai

Yair Goldberg

Daniel Gill

Israel Feldman

Song Song

Michael Reich

Izhar Bargad,

Alon Kaufman

Daniel Nevo

Yonatan Woodbridge

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My birds

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Das große Karthago führte drei Kriege.

Nach dem ersten war es noch mächtig.

Nach dem zweiten war es noch bewohnbar.

Nach dem dritten war es nicht mehr aufzufinden.-Bertolt  Brecht

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