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The course is divided into two halves, the first covers probability theory and the second covers statistics. The course covers: Sample space, Events, Basic set theory, Axioms of probability. Conditional probability, Independent events…

Basic probability theory, random variables in one and several dimensions, multivariate Gaussian distribution, convergence of random variables and distributions, conditional distributions. Moment generating functions and characteristic…

The course treats: Markov chains: model graphs, Markov property, transition probabilities, persistent and transient states, positive and null persistent states, communication, existence and uniqueness of stationary distribution, and…

The course treats stochastic processes in discrete and continuous time. The main elements are: Models for stochastic dependence.Concepts of description of stationary stochastic processes in the time domain: expectation, covariance, and…

The student chooses in consultation with supervisors and examiner an independent examination assignment comprising 15 credits. The assignment can either be linked to current scientific projects at the Division of Mathematical Statistics or…

The course gives an overview of simulation based methods of statistical analysis. Markov chain methods for complex problems, e.g. Gibbs sampling and the Metropolis-Hastings algorithm. Bayesian modelling and inference. The re-sampling…

The course is given during the autumn semester at Lunds university and at the Technical University of Denmark in Lyngby. The graduate course in Advanced Time Series Analysis has its target audience amongst students with technical or…

Extreme value theory concerns mathematical modelling of extreme events. Recent developments have introduced very flexible and theoretically well motivated semi-parametric models for extreme values which now are at the stage where they can…

Time series analysis concerns the mathematical modelling of time varying phenomena, e.g., ocean waves, water levels in lakes and rivers, demand for electrical power, radar signals, muscular reactions, ECG-signals, or option prices at the…

The course deals with model building and estimation in non-linear dynamic stochastic models for financial systems. The models can have continuous or discrete time and the model building concerns determining the model structure as well as…

Least squares and maximum-likelihood-method; odds ratios; Multiple and linear regression; Matrix formulation; Methods for model validation, residuals, outliers, influential observations, multi co-linearity, change of variables; Choice of…

Bayesian methods for stochastic modelling, classification and reconstruction. Random fields, Gaussian random fields, Kriging, Markov fields, Gaussian Markov random fields, non-Gaussian observations. Covariance functions, multivariate…

Basic definitions. Continued study of AR (auto regressive), MA (moving average) and ARMA-processes. Line spectrum and parametric estimating methods. Sub space based techniques. Non-parametric spectral estimators, data-adaptive techniques…

The course consists of two related parts. In the first part we will look at option theory in discrete time. The purpose is to quickly introduce fundamental concepts of financial markets such as free of arbitrage and completeness as well as…

The course treats: The real numbers: axioms, examples of proofs of basic arithmetical rules. The elementary functions, polynomials, rational functions, the exponential function and the natural logarithm, the trigonometric functions…

The course treats: Elementary logic and set theory Basic properties of the natural numbers and the integers: induction, divisibility, Euclid’s algorithm Basic properties of polynomials: divisibility, Euclid’s algorithm Complex…

The course treats: Functions of several variables, basic topology in R^n. Continuity, theorems about continuous functions. Differentiable functions, gradients and directional derivatives. Taylor's formula. Extreme values…

Variable substitution, inverse and implicit functions, curve and surface integrals, Green's formula, Gauss Divergence Theorem, Stokes Theorem are treated.

The course treats Matrices: matrix operations, matrix inverse, matrix rank Determinants: definition and properties Linear spaces: subspace, span, linear dependence/independence, basis, dimension Euclidean spaces: scalar product,…

The course treats: Properties of the real numbers R: completeness axiom, Cauchy sequences, cardinality of rational and irrational numbers. Topology in Rn: open and closed sets, p-norms, convergence, compactness and the Bolzano…

The course treats: Basic properties of Fourier series of functions in one variable. Exponential form and trigonometric form. Riemann-Lebesgue lemma. Elementary conditions for pointwise and uniform convergence. Gibbs phenomenon. Basic…

The course treats: Number theory: divisibility, prime numbers, the Euclidean algorithm, Chinese remainder theorem, modular arithmetic Sets, functions and relations, equivalence relations Combinatorics: the four cases of counting with…

The aim of the course is to give necessary knowledge of digital image analysis for further research within the area and to be able to use digital image analysis within other research areas such as computer graphics, image coding, video…

The course treats basic theory of analytic functions: Elementary properties of analytic functions in one variable. Complex differentiability and Cauchy-Riemann equations. Calculation rules. Elementary examples of analytic functions:…

The course treats: Existence and uniqueness of solutions to initial value problems for systems of ordinary differential equations. Approximation of solutions and continuous dependence on parameters. Linear systems with variable and…

The course treats variational problems with and without constraints, Euler equations with and without constraints, Legendre, Jacobi and Weierstrass necessary condition for local minimum, Hilbert invariant integral and Weierstrass…

The course treats: Number theory: the fundamental theorem of arithmetic, modular artithmetic. Groups: definition, basic examples of groups, subgroups, normal subgroups, factor groups, isomorphisms and homomorphisms, Lagrange's theorem,…

The course treats multiplicative number theoretic functions, Möbius inversion formula, properties of Euler's totient function, primitive roots and indices, quadratic residues, the Legendre symbol and its properties, the quadratic…

The course treats: quadratic forms and matrix factorisation, convexity, separating planes and Farkas’ Lemma, the theory of optimization with and without constraints, Lagrange functions, Karush-Kuhn-Tucker theory, duality, methods for…

The course comprises: Matrices and determinants. Linear spaces. Spectral theory.The Jordan normal form. Matrix factorizations. Matrix polynomials and matrix functions. Norms. Scalar products. Singular values. Normal matrices…

The degree project requires a literature survey and specialised studies. Furthermore, a number of compulsory activities are included, in the form of teaching sessions and seminars that treat e.g. scientific writing in English and Swedish,…

The degree project requires a literature review and special studies. In addition, it includes a number of compulsory elements, in the form of lessons and seminars, which deal with, among other things, scientific writing in English and…

A central part of the course is existence- and uniqueness theorems about measures defined on sigma-algebras, integration theory, conditional expectation and weak convergence in metric spaces.

The course treats: Convergence of sequences of analytic functions. Locally uniform convergence, normal families, Montel’s theorem. In-depth study of conformal mappings. Riemann sphere, stereographic projection, Möbius…

The course treats the geometry of curves and surfaces, especially in three dimensions. In particular, we study the concepts of curvature and torsion. The course covers: The geometry of curves in Euclidean space, their curvature and…

The course treats: Finitely generated groups: free groups, Nielsen-Schreier Theorem, group presentations, finitely presented groups. Free products: free products with amalgamation, HNN extensions. Solvable groups: polycyclic groups,…

The course treats: topological spaces and metric spaces with examples, product topologies, continuity of functions, connectedness, completeness, and compactness, including the Arzela-Ascoli Theorem, examples of applications and topological…

The course treats: Fourier series, Fourier transform and finite Fourier transform, L^2 convergence of Fourier series, pointwise convergence, Cesàro means and Fejer’s theorem, Weyl’s criterion, the Fourier inversion theorem, Parseval’s and…

This course treats the general notion of a measure defined on a sigma-algebra, construction of measures with help of outer measures, in particular the Lebesgue measure in Rd. These concepts are then used to define the integral of a…

The course treats: Linear systems of ordinary differential equations in the complex plane. Power series solutions. Singular points. Frobenius method. Some classical differential equations and special functions. Boundary value…

The course covers: Differentiable manifolds, their tangent spaces and tangent bundles. Riemannian metrics and their unique Levi-Civita connection. Geodesics and the important Riemann curvature tensor and its influence on the local…

The course treats: • homotopy theory, the fundamental group, covering spaces • the Brouwer fixed point theorem, the Borsuk-Ulam theorem • deformation retracts, fundamental groups and homology of surfaces • surgery of manifolds, also called…

The course treats: Group representations: linear representations, equivalent representations, regular representation, induced and restricted representations, irreducible representations, Maschke’s Theorem, dual representations and…

The course treats: Groups: Permutation groups. Burnside's lemma with application to Pólya arithmetic. Sylow's theorems. Symmetric and alternating groups. The structure of finitely generated Abelian groups. Rings: Noetherian and…

The course treats fundamental properties of Banach and Hilbert spaces and the bounded linear operators defined on them: Banach spaces, the Hahn-Banach Theorem, weak convergence and  weak precompactness of the unit ball. Hilbert…

The course treats: The method of characteristics and nonlinear equations of the first order. Laplace’s equation. The heat equation. The wave equation. The Cauchy–Kowalevski theorem. Sobolev spaces. Existence, uniqueness and…

The course treats basic properties of signed and complex measures: Hahn and Jordan decomposition, absolute continuity and the Radon-Nikodym theorem, singularity, Lebesgue decomposition of measures, differentiability of finite Borel…

The course treats applications of the Hahn-Banach theorem, weak convergence and compactness, the Riesz representation theorem, the use of orthonormal bases, boundedness, compactness and spectra of integral operators, the…