The Net Advance of Physics

The Net Advance of Physics:
STATISTICAL METHODS

General: Introductory: Schmittmann and Zia 99/05;
General: Textbooks:
- Statistics: Methods and Applications by T. Hill and P. Lewicki [Tulsa: StatSoft, 2007]
- Statistical Inference by Konstantin Zuev [2016/03] ACM lecture notes, 145 pp.
General:
- NIST/SEMATECH e-Handbook of Statistical Methods [2006/07]
- Probability and Statistics WWW Resources from Zombeck's Handbook of Space Astronomy and Astrophysics [Cambridge University Press]
- Probability and Statistical Inference by Harrison B. Prosper [2005/03]
- Introduction to Randomness and Statistics by Alexander K. Hartmann [2009/10] 95pp.
- Probability and Statistics for Particle Physicists by José Ocariz [2014/05]
- Practical Statistics for Particle Physicists by Harrison B. Prosper [2015/04]
- Statistical sensitiveness for science by Jose D. Perezgonzalez [2016/04]
- Practical Statistics for Particle Physics by Luca Lista [2016/09]
- Advances in Variational Inference by Cheng Zhang et al. [2017/11]
- Lectures on Statistics in Theory: Prelude to Statistics in Practice by Robert D. Cousins [2018/07]
- An Introduction to Inductive Statistical Inference: From Parameter Estimation to Decision Making by Henk van Elst [2018/08] 149 pp.
- An Overview of Statistical Data Analysis by Rui Portocarrero Sarmento and Vera Costa [2019/08]
- Theory of probability and statistics as exemplified in short dictums by Oscar Sheynin [2021/07]
Types: BAYESIAN; MONTE CARLO;
Type: ALGEBRAIC:
- Algebraic Statistics in Practice: Applications to Networks by Marta Casanellas et al. [2019/06]
Type: ALGORITHMIC:
- Algorithmic statistics: forty years later by Nikolai Vereshchagin and Alexander Shen [2016/07]
Type: BOOSTED DECISION TREE:
- Topics in statistical data analysis for high-energy physics by G. Cowan [2009/06]
Type: FISHER:
- Fisher Matrices and Confidence Ellipses: A Quick-Start Guide and Software by Dan Coe [2009/06]
Type: INTERVAL CALCULUS: Gutowski 2003/02;
Type: LARGE DEVIATION:
- A basic introduction to large deviations: Theory, applications, simulations by Hugo Touchette [2011/06]
- Large deviations by Satya N. Majumdar and Gregory Schehr [2017/11]
Aspects: MARKOV PROCESSES; RANDOM SAMPLING;
Aspects: BENFORD'S LAW:
- The Mathematics of Benford's Law: A Primer by Arno Berger and Theodore P. Hill [2019/09]
Aspects: BOOTSTRAPPING:
- What Teachers Should Know about the Bootstrap: Resampling in the Undergraduate Statistics Curriculum by Tim Hesterberg [2014/11]
Aspects: BRANCHING PROCESSES:
- Introductory Lectures on Stochastic Population Systems by Donald A. Dawson [2017/05] 256 pp.
Aspects: CAUSALITY:
- An Introduction to Flexible Methods for Policy Evaluation by Martin Huber [2019/10]
Aspects: CORRELATIONS:
- A Tutorial on Canonical Correlation Methods by Viivi Uurtio et al. [2017/11]
- Asymptotics of Correlations in the Ising Model: A Brief Survey by Sébastien Ott and Yvan Velenik [2019/05]
- Everything you wish to know about correlations but are afraid to ask by T. S. Grigera [2020/02]
Aspects: DATA FILTERING:
- The Hitchhiker's Guide to Nonlinear [Data] Filtering by Anna Kutschireiter et al. [2019/03]
Aspects: EXPERIMENTAL UNCERTAINTY:
- Annotated Bibliography of Some Papers on Combining Significances or p-values by Robert D. Cousins [2007/05]
- A Reckless Guide to P-Values: Local Evidence, Global Errors by Michael J. Lew [2019/10]
Aspects: EXTREMES:
- Extremes and Records by Sanjb Sabhapandit [2019/06]
Aspects: FALSE CONFIDENCE THEOREM:
- An Exposition of the False Confidence Theorem by Iain Carmichael and Jonathan P. Williams [2018/07]
Aspects: FANO'S INEQUALITY:
- An Introductory Guide to Fano's Inequality with Applications in Statistical Estimation by Jonathan Scarlett and Volkan Cevher [2019/01]
Aspect's: De FINETTI'S THEOREM:
- De Finetti for undergraduates by D. Mundici [2021/07]
Aspects: FIRST PASSAGE TIME:
- First Passage processes in cellular biology by Srividya Iyer-Biswas and Anton Zilman [2015/03]
- Brownian Motion and Beyond: First-Passage, Power Spectrum, Non-Gaussianity, and Anomalous Diffusion by Ralf Metzler [2019/08]
- Preface: New trends in first-passage methods and applications in the life sciences and engineering by D. S. Grebenkov et al. [2020/11]
Aspects: HAWKES PROCESSES:
- Hawkes Processes by Patrick J. Laub et al. [2015/07]
Aspects: KERNEL-DENSITY ESTIMATION:
- A Tutorial on Kernel Density Estimation and Recent Advances by Yen-Chi Chen [2017/04]
Aspects: MODE:
- The Modal Age of statistics by José E. Chacón [2018/07]
Aspects: MULTIPLE IMPUTATION:
- Multiple Imputation: A Review of Practical and Theoretical Findings by Jared S. Murray [2018/01]
Aspects: POINT PROCESSES:
- A Review of Self-Exciting Spatio-Temporal Point Processes [in Statistics] and Their Applications by Alex Reinhart [2017/08]
- Self-Exciting Point Processes: Infections and Implementations by Sebastian Meyer [Statistical Science 33, 327 (2018)]
Aspects: RARE EVENTS:
- Rare Event Simulation by James L. Beck and Konstantin M. Zuev [2015/08]
Aspects: RECORDS (i.e. data points far from norm):
- Records in stochastic processes -- Theory and applications by Gregor Wergen [2012/11]
Aspects: REGRESSION:
- Extremal Quantile Regression: An Overview by Victor Chernozhukov et al. [2016/12]
Aspects: STATISTICAL SIGNIFICANCE and HYPOTHESIS TESTING: Sinervo 2002/08;
- R. A. Fisher, design theory, and the Indian connection by A. R. P. Rau [J. Biosci. 34, 353 (2009)]
- Introduction to Randomness and Statistics by Alexander K. Hartmann [2009/10] 95pp.
- Variational Inference: A Review for Statisticians by David M. Blei et al. [2016/01]
- A review on statistical inference methods for discrete Markov random fields by Julien Stoehr [2017/04]
- Advances in Variational Inference by Cheng Zhang et al. [2017/11]
- Lectures on Statistics in Theory: Prelude to Statistics in Practice by Robert D. Cousins [2018/07]
- An Introduction to Inductive Statistical Inference: From Parameter Estimation to Decision Making by Henk van Elst [2018/08] 149 pp.
Type: FIDUCIAL:
- Introduction to generalized fiducial inference by A. C. Murph et al. [2023/02]
Re: ASTRONOMY:
- Statistics in astronomy by Eric D. Feigelson [Encyclopedia for Statistical Science, 2009]
- Statistical Methods for Astronomy by Eric D. Feigelson and G. Jogesh Babu [2012/05]
- Statistical methods in astronomy by James P. Long and Rafael S. de Souza [2017/07]
Re: COMPUTATIONAL GEOMETRY:
- Statistical depth meets computational geometry: a short survey by Peter J. Rousseeuw and Mia Hubert [2015/08]
Re: COSMOLOGY:
- A practical guide to Basic Statistical Techniques for Data Analysis in Cosmology by Licia Verde [2007/12]
- Statistical methods in cosmology by Licia Verde [2009/11]
Re: GENETICS:
- Marginal likelihoods in phylogenetics: a review of methods and applications by Jamie R. Oaks et al. [2018/05]
Re: HIGH-ENERGY PHYSICS:
- Statistics for Searches at the LHC by Glen Cowan [2012/09]
- Probability and Statistics for Particle Physicists by José Ocariz [2014/05]
- Practical Statistics for the LHC by Kyle Cranmer [2015/03]
- Practical Statistics [for High Energy Physics] by L. Lyons [2015/03]
- Practical Statistics for Particle Physicists by Harrison B. Prosper [2015/04]
- Practical Statistics for Particle Physics by Luca Lista [2016/09]
- Practical Statistics for Particle Physics by Roger John Barlow [2019/05]
Re: LARGE SCALE COSMIC STRUCTURE: Borgani 95/10;
Re: MINKOWSKI FUNCTIONALS: Schmalzing et al. 95/08;
Re: QUANTUM DOTS: Alhassid 2001/02;
Re: RANDOM MATRICES:
- A review of exact results for fluctuation formulas in random matrix theory by P. J. Forrester [2022/04]

THE NET ADVANCE OF PHYSICS