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Mathematical statistics --- Informatique --- Statistique --- Data processing --- Méthodes statistiques --- Computational statistics --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistical methods --- Statistics --- Probabilities --- Sampling (Statistics)

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Bootstrapping is a conceptually simple statistical technique to increase the quality of estimates, conduct robustness checks and compute standard errors for virtually any statistic. This book provides an intelligible and compact introduction for students, scientists and practitioners. It not only gives a clear explanation of the underlying concepts but also demonstrates the application of bootstrapping using Python and Stata.

Python (Computer program language) --- Computer bootstrapping. --- Booting, Computer --- Bootstrapping, Computer --- Computer booting --- Computer systems --- Scripting languages (Computer science) --- Bootstrapping. --- Computational Statistics. --- Resampling. --- Variance Estimation Methods.

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Statistics as Topic. --- Software. --- Algorithms. --- Statistics --- Data processing --- Computer programs --- Computer programs. --- Data processing. --- Earth Sciences --- Information Technology --- Mathematical Sciences --- Geographic Information Systems & Remote Sensing --- General and Others --- Applied Mathematics --- Stochastic Computation --- statistics --- statistical software --- statistical computing --- computational statistics

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This book covers a broad range of research results in the field of Markov and Semi-Markov chains, processes, systems and related emerging fields. The authors of the included research papers are well-known researchers in their field. The book presents the state-of-the-art and ideas for further research for theorists in the fields. Nonetheless, it also provides straightforwardly applicable results for diverse areas of practitioners.

Monte Carlo --- MCMC --- Markov chains --- computational statistics --- bayesian inference --- Non-Homogeneous Markov Systems --- Markov Set Systems --- limiting set --- tail expectation --- asymptotic bound --- quasi-asymptotic independence --- heavy-tailed distribution --- dominated variation --- copula --- branching process --- migration --- continuous time --- generating function --- period-life --- reliability --- redundant systems --- preventive maintenance --- multiple vacations --- process mining --- process modelling --- phase-type models --- process target compliance --- particle filter --- missing data --- single imputation --- impoverishment --- Markov Systems --- open population Markov chain models --- Semi-Markov processes --- controllable Markov jump processes --- compound Poisson processes --- diffusion limits --- stochastic control problem with incomplete information --- novel queuing models in applications --- semi-Markov model --- Markov model --- hybrid semi-Markov model --- manpower planning --- semi-Markov modeling --- occupancy --- first passage time --- duration --- non-homogeneity --- DNA sequences --- state space model --- Kalman filter --- constrained optimization --- two-sided components --- basketball --- Markov chain --- second order --- off-ball screens --- performance --- semi-Markov --- transient analysis --- asymptotic analysis --- n/a

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This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases, or large in numbers of variables, or large in both. All ideas are illustrated with displays from analyses of real datasets and the importance of interpreting displays effectively is emphasized. Graphics should be drawn to convey information and the book includes many insightful examples. New approaches to graphics are needed to visualize the information in large datasets and most of the innovations described in this book are developments of standard graphics. The book is accessible to readers with some experience of drawing statistical graphics.

Artificial intelligence. Robotics. Simulation. Graphics --- Information systems --- QA 276.3 Graphic methods --- Computational Science & Engineering --- Computational Statistics --- Computer Imaging, Graphics & Vision --- Computer Science --- Statistics --- Computer graphics. --- Statistique --- Infographie --- Graphic methods. --- Méthodes graphiques --- Computer graphics --- Graphic methods --- Statistics -- Graphic methods. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Méthodes graphiques --- EPUB-LIV-FT LIVSTATI SPRINGER-B --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Diagrams, Statistical --- Statistical diagrams --- Mathematics. --- Operations research. --- Decision making. --- Data mining. --- Visualization. --- Computer software. --- Statistics. --- Mathematical Software. --- Statistical Theory and Methods. --- Data Mining and Knowledge Discovery. --- Operation Research/Decision Theory. --- Computer Graphics. --- Computer art --- Graphic arts --- Electronic data processing --- Engineering graphics --- Image processing --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Software, Computer --- Computer systems --- Visualisation --- Imagery (Psychology) --- Imagination --- Visual perception --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Math --- Science --- Digital techniques --- Decision making --- Curve fitting --- Mathematical statistics. --- Operations Research/Decision Theory. --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Statistics . --- Statistics - Graphic methods