Statistical Modeling Using Local Gaussian Approximation

ISBN-13: 9780128158616 / Angielski / Miękka / 2021 / 460 str.

Dag Bjarne Tjostheim; Hakon Otneim; Bard Stove

Spis treści

1. Introduction
2. Parametric, nonparametric, locally parametric
3. Dependence
4. Local Gaussian correlation and dependence
5. Local Gaussian correlation and the copula
6. Applications in finance
7. Measuring dependence and testing for independence
8. Time series dependence and spectral analysis
9. Multivariate density estimation
10. Conditional density estimation
11. The local Gaussian partial correlation
12. Regression and conditional regression quantiles
13. A local Gaussian Fisher discriminant

O autorze

Dag Tjøstheim is Emeritus Professor, Department of Mathematics, University of Bergen. He has a PhD in applied mathematics from Princeton University (1974). He has authored more than 120 papers in international journals. He is a member of the Norwegian Academy of Sciences and has received several prizes for his scientific work. His main interests are in econometrics, nonlinear time series, nonparametric methods, modeling of dependence, spatial variables, and fishery statistics. Håkon Otneim is Associate Professor at the Norwegian School of Economics. He has a PhD in statistics from the University of Bergen (2016). He has published papers in international journals about multivariate density estimation and conditional density estimation. His research interests include development and application of non- and semiparametric statistics, statistical programming, and data visualization. Bård Støve is Professor of Statistics at the University of Bergen. He received his PhD degree in Statistics, 2005. He was Assistant Professor at the Norwegian School of Economics (2007--2011) and worked as an Actuary in a consulting firm (2005--2007). He has been working on the development of nonparametric models and application of such models to areas in finance and economics. He has published several research papers in journals such as Econometric Theory and Scandinavian Journal of Statistics.