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Author: Jürgen PilzSimulation results indicate that k = 6 is the optimal value, where αact is below but close to αnom. ... As a result, we obtain: Statistical Simulation for the Sequential Triangular Test H0: rho <= 0.3 versus H1: rho > 0.3 Nominal ...
Author: Alberto RotondiThis agreement increases our confidence in the least squares algorithms, even with non-Gaussian data. Simulation thus demonstrates an important fact: the deviations from the Gaussian model are small. Ultimately, a negligible error is ...
Author: Matthias TemplHarness actionable insights from your data with computational statistics and simulations using RAbout This Book* Learn five different simulation techniques (Monte Carlo, Discrete Event Simulation, System Dynamics, Agent-Based Modeling, and ...
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Author: Carlo GaetanThis book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto ...
Author: Ding-Geng ChenThis book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications.
Author: Brian D. RipleyWith these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .this is a very competently written and useful ...
Author: Timothy C. HaasA companion website featuring all R code and data used throughout the book. Solutions to all exercises are presented along with an online intelligent tutoring system that supports readers who are using the book for self-study.
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Author: Rick WicklinThis book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques.
