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Quantitative methods (economics) --- Time-series analysis --- Econometric models --- 330.115 --- 681.33 --- 519.2 --- 519.55 --- Econometrics --- Mathematical models --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities --- Kwantitatieve methoden (economie) --- Programmering --- Probability. Mathematical statistics --- Econometric models. --- Time-series analysis. --- 519.2 Probability. Mathematical statistics

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Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R. "Its biggest advantage is that it aims only to teach R...It organizes R commands very efficiently, with much teaching guidance included. I would describe this book as being handy--it's the kind of book that you want to keep in your jacket pocket or backpack all the time, ready for use, like a Swiss Army knife." (Loveday Conquest, University of Washington) "Whilst several books focus on learning statistics in R..., the authors of this book fill a gap in the market by focusing on learning R whilst almost completely avoiding any statistical jargon...The fact that the authors have very extensive experience of teaching R to absolute beginners shines throughout." (Mark Mainwaring, Lancaster University) "Exactly what is needed...This is great, nice work. I love the ecological/biological examples; they will be an enormous help." (Andrew J. Tyne, University of Nebraska-Lincoln) Alain F. Zuur is senior statistician and director of Highland Statistics Ltd., a statistical consultancy company based in the UK. He has taught statistics to more than 5000 ecologists. He is honorary research fellow in the School of Biological Sciences, Oceanlab, at the University of Aberdeen, UK. Elena N. Ieno is senior marine biologist and co-director at Highland Statistics Ltd. She has been involved in guiding PhD students on the design and analysis of ecological data. She is honorary research fellow in the School of Biological Sciences, Oceanlab, at the University of Aberdeen, UK. Erik H.W.G. Meesters is a researcher at the Dutch Institute for Marine Resources and Ecosystem Studies (IMARES). He specializes in coral reef ecology and applied statistics and conducts research on North Sea benthos and seal ecology.

Computer. Automation --- Biomathematics. Biometry. Biostatistics --- informatica --- biostatistiek --- statistiek --- medische statistiek --- ecologie --- R (Computer program language) --- Mathematical statistics --- Data processing --- Statistics --- Science --- Statistical methods --- Programming --- 519.55 --- GNU-S (Computer program language) --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Domain-specific programming languages --- Probabilities --- Sampling (Statistics)

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This handbook presents a collection of survey articles from a statistical as well as an econometric point of view on the broad and still rapidly developing field of financial time series. It includes most of the relevant topics in the field, from fundamental probabilistic properties of financial time series models to estimation, forecasting, model fitting, extreme value behavior and multivariate modeling for a wide range of GARCH, stochastic volatility, and continuous-time models. The latter are especially important for modeling high frequency and irregularly observed financial time series and provide the foundation for estimating realized volatility. Cointegration and unit roots, which are extremely important concepts for understanding and modeling nonstationary time series, and several further relevant topics in the field of financial time series (i.e. nonparametric methods, copulas, structural breaks, high frequency data, resampling and bootstrap methods, and model selection for financial time series among others) are included in detail. All contributions are clearly written and provide, in a pedagogical manner, a broad and detailed overview of the major topics within financial time series.

Finance --- Time-series analysis. --- Statistical methods. --- Statistics. --- Econometrics. --- Finance. --- Mathematical statistics. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Quantitative Finance. --- Statistics and Computing/Statistics Programs. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Funding --- Funds --- Economics --- Currency question --- Economics, Mathematical --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics . --- Economics, Mathematical . --- Mathematical economics --- Methodology --- Finance - Statistical methods --- Time-series analysis --- AA / International- internationaal --- 305.970 --- 305.91 --- 330.3 --- 305.971 --- 304.0 --- -Time-series analysis --- 519.55 --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Algemeenheden: Autoregression and moving average representation. ARIMA. ARMAX. Lagrange multiplier. Wald. Function (mis) specification. Autocorrelation. Homoscedasticity. Heteroscedasticity. ARCH. GARCH. Integration and co-integration. Unit roots --- Econometrie van de financiële activa. Portfolio allocation en management. CAPM. Bubbles --- Methode in staathuishoudkunde. Statische, dynamische economie. Modellen. Experimental economics --- Speciale gevallen in econometrische modelbouw --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen