Matematikprogrammer og statistikprogrammer

With a quick start guide to epidemiological data visualization and analysis in R, this book spans the gulf between academia and practices providing many lively, instructive data analysis examples using the most up-to-date data, such as the newly discovered COVID-19.

Das Buch richtet sich an diejenigen, die Statistik in wirtschaftswissenschaftlich orientierten Studiengangen studieren. Der leicht verstandliche Text ist mit vielen Beispielen und Ubungen erganzt. Die praxisnahe Darstellung der Methoden wird durch die Erklarung und Anwendung der Statistikprogramme R (open source Progamm) und SPSS vervollstandigt. Im Text sind fur beide Programme viele Programmanweisungen enthalten. Die Autoren haben kompakt alle elementaren statistischen Verfahren fur die Okonomie anschaulich erklart.

Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. To help readers to get familiar with the features of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software and applications. It is built up incrementally, starting with a summary of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach is used to describe the R tools for LMMs. All the classes of linear models presented in the book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariance structure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text.

Essentials of Mathematica: With Applications to Mathematics and Physics, based on the lecture notes of a course taught at the University of Illinois at Chicago to advanced undergraduate and graduate students, teaches how to use Mathematica to solve a wide variety problems in mathematics and physics. The text assumes no previous exposure to Mathematica. It is illustrated with many detailed examples that require the student to construct meticulous, step-by-step, easy-to-read Mathematica programs. It includes many detailed graphics, with instructions to students on how to achieve similar results. The aim of Essentials of Mathematica is to provide the reader with Mathematica proficiency quickly and efficiently. The first part, in which the reader learns how to use a variety of Mathematica commands, avoids long discussions and overly sophisticated techniques. The second part covers a broad range of applications in physics and applied mathematics, including negative and complex bases, the double pendulum, fractals, the logistic map, the quantum harmonic oscillator, the quantum square potential, the Van der Pol oscillator, the Duffing oscillator, multilane bidirectional pedestrian traffic, public-key encryption, tautochrone curves, Iterated function systems, motion of a bead on a rotating circle, Mersenne and perfect numbers, Lindenmayer systems, skydiving, Lorenz equations, the Foucault's pendulum, and Julia and Mandelbrot sets.

The Maple Summer Workshop and Symposium, MSWS '94, reflects the growing commu- nity of Maple users around the world. This volume contains the contributed papers. A careful inspection of author affiliations will reveal that they come from North America, Europe, and Australia. In fact, fifteen come from the United States, two from Canada, one from Australia, and nine come from Europe. Of European papers, two are from Ger- many, two are from the Netherlands, two are from Spain, and one each is from Switzerland, Denmark, and the United Kingdom. More important than the geographical diversity is the intellectual range of the contributions. We begin to see in this collection of works papers in which Maple is used in an increasingly flexible way. For example, there is an application in computer science that uses Maple as a tool to create a new utility. There is an application in abstract algebra where Maple has been used to create new functionalities for computing in a rational function field. There are applications to geometrical optics, digital signal processing, and experimental design.

Tahmin modellerini sorumlu bir yaklä¿mla nas¿l kurabiliriz? Bu, farkl¿ deneyim seviyelerindeki veri bilimciler taraf¿ndan bana s¿kl¿kla sorulan bir sorudur. Görünü¿te basit ama ayn¿ zamanda zorlay¿c¿, çünkü ele al¿nmas¿ gereken farkl¿ paydälara ait birkaç ortogonal konu ve bak¿¿ aç¿s¿ var.Model geli¿tiriciler, model e¿itiminin otomasyonuna, performans¿n¿n izlenmesine, hata ay¿klamaya ve MLOps ile ilgili di¿er konulara odaklan¿r. Tahmin modelleri kullan¿c¿lar¿ aç¿klanabilirlik, ¿effafl¿k ve güvenlikle daha fazla ilgilenirken, adalet, önyarg¿, etik ise çöunlukla toplumu ilgilendiren konulard¿r. Düzenleyiciler, özellikle büyük ölçekli etkileri olan model kullan¿mlar¿n¿n sonuçlar¿ ile ilgilenmektedir.Bu bak¿¿ aç¿lar¿n¿ dikkate alarak, Sorumlu Makine Ö¿renmesi (RML) ile ilgili üç temel unsura odaklan¿yoruz.Algoritmalar - Genellikle, verideki karmä¿k ili¿kileri ortaya ç¿karmak için geli¿mi¿ ve esnek makine ö¿renmesi algoritmalar¿ kullanman¿z gerekir. Ancak, nas¿l çal¿¿t¿klar¿ anlä¿lmadan kullan¿lmamal¿d¿r. Do\-la\-y¿\-s¿y\-la sorumlu modelleme hakk¿nda bir tart¿¿ma, karmä¿k modellerin nas¿l çal¿¿t¿¿¿ konusuna mutlaka de¿inmelidir.Yaz¿l¿m - Geli¿mi¿ modellerin e¿itimi, yöun hesaplama gerektiren bir süreçtir. Verimli e¿itime izin veren paketler, birer mühendislik harikas¿d¿r. Profesyoneller iyi araçlar kullan¿r, bu nedenle sorumlu modellemeyle ilgili bir hikaye yaz¿l¿rsa, mutlaka iyi yaz¿l¿mla ilgili bir bölüm içermelidir.Süreç - Tahmin modelleri kurmak yaln¿zca araçlarla ilgili de¿il, ayn¿ zamanda planlama, lojistik, ileti¿im, teslim tarihleri ve hedeflerle de ilgilidir. Veri ve model ke¿fi süreci tekrarl¿ bir süreçtir, her tekrarda oldüu gibi, giderek daha iyi modellere ulä¿r¿z. Araçlar¿ ne zaman ve nas¿l kullanacä¿n¿z¿ bilmiyorsan¿z, yaln¿zca araçlar¿ kullanabilmek yeterli olmaz. Bu nedenle sorumlu modellemeden önce modelleme süreçlerin ele al¿nmas¿ gerekiyor.Bu kitap, bahsedilen bu yönleri ayn¿ anda bir araya getiren bir içeri¿e sahiptir. ¿çeri¿i, baz¿ modern makine ö¿renmesi yöntemlerini ve çal¿¿ma mekanizmalar¿ndan olümaktad¿r. Yöntemler, R dilinde Rcran yaz¿lm¿¿ örnek kodlarla desteklenmi¿tir. Beta ve Bit adl¿ iki karakterin maceralar¿n¿ anlatan bir çizgi roman ile anlat¿m hikayele¿tirilmi¿tir. Bu etkile¿im, farkl¿ bir model denemek, ke¿if için bäka bir yöntem denemek, veya bäka verileri aramak gibi analistlerin s¿kl¿kla kar¿¿ kar¿¿ya kald¿klar¿, modeller nas¿l kar¿¿lät¿r¿l¿r veya nas¿l dörulan¿r

Dieses Buch richtet sich an Studierende verschiedener Fachrichtungen, die das Softwarepaket Octave als kostenfreien und praktischen Lernassistenten nutzen mochten. Es stellt dar, wie sich Octave zur Losung mathematischer Probleme aus technischen und ingenieurwissenschaftlichen Anwendungen einsetzen lasst. Nebenbei konnen mit diesem Buch elementare Programmierkenntnisse erlernt oder aufgefrischt werden. Da Octave Parallelen zu dem kostenpflichtigen, haufig auf Rechnerarbeitsplatzen in Hochschulen und forschungsorientierten Einrichtungen installierten Softwarepaket MATLAB aufweist, lassen sich die in diesem Buch besprochenen Inhalte und Methoden bequem in die Hochschule und daruber hinaus in die spatere Berufspraxis ubertragen. Das Buch eignet sich damit auch fur Anwender, die in ihrem Berufsleben mathematische Probleme mit Octave oder MATLAB zu losen haben.Behandelt werden die wichtigsten Grundlagen und Methoden von Octave: elementare Rechnungen mit reellen und komplexen Zahlen, die besonders wichtige Arbeit mit Matrizen und Vektoren, die Arbeit mit Zeichenketten, die Losung von linearen Gleichungssystemen, die Erstellung von Grafiken mit und ohne animierten Inhalten, die Nutzung und die eigene Programmierung von Octave-Skripten und Octave-Funktionen. Lernenden wird an ausgewahlten Beispielen aus den Bereichen Lineare Algebra, Analysis und numerische Mathematik erlautert, wie Octave zur Uberprufung und Korrektur von Rechenergebnissen bzw. Rechenwegen sowie zum Verstehen und Entdecken von mathematischen Sachverhalten eingesetzt werden kann. Auerdem werden die Losung linearer und nichtlinearer Optimierungsprobleme, die Approximation von Daten und Funktionen (Methode der kleinsten Quadrate, Interpolation mit Polynomen und Splines), die Losung nichtlinearer Gleichungssysteme sowie ausgewahlte Grundlagen der beschreibenden Statistik und Wahrscheinlichkeitsrechnung behandelt.Ubungsaufgaben laden zum Mitmachen ein und helfen, die besprochenen Inhalte zu verstehen, anzuwenden und auf die Aufgaben und Probleme aus den eigenen Mathematikvorlesungen zu ubertragen. Zu jeder Aufgabe gibt es mehr oder weniger ausfuhrliche Musterlosungen. Zusatzmaterialien zum Download erganzen das Buch, wobei die enthaltenen Skripte und Funktionen von den Lesern als Ausgangspunkt fur eigene Programmiertatigkeiten genutzt werden konnen und sollen.

MuPAD ist ein Computeralgebra-System, mit dem nicht nur Problemstellungen der Mathematik sondern auch mathematische Aufgaben in den Natur- und Ingenieurwissenschaften behandelt werden konnen. Das Tutorium fur Einsteiger fuhrt grundlegend in MuPAD ein (ab Version 3.0.). In nachvollziehbaren Schritten werden die wichtigsten Bausteine vorgestellt. Systemfunktionen, Graphik sowie Programmierung konnen Nutzer anhand zahlreicher Beispiele einuben. Zukunftige Anderungen und Erweiterungen werden unter http://www.mupad.de/doc.html dokumentiert.

Algebra Interactive! is an HTML-based course for undergraduate students in all fields of science, e.g. mathematics, computer science, physics and (electrical) engineering. The novel features of Algebra Interactive are the interactive examples and tools for computing in the various structures. Many of these tools and examples use the computer package GAP, which comes with Algebra Interactive, as a back engine. Moreover, abstract notations are enlivened by Java applets, which go beyond the classical examples given in traditional textbooks. The course contains numerous exercises. Apart from the classical type of exercise (with hints and solutions), the product also presents interactive multiple-choice questions on each page and at the end of each chapter. A comprehensive accompanying printed book summarizes the contents of Algebra Interactive.

Looking back at the years that have passed since the realization of the very first electronic, multi-purpose computers, one observes a tremendous growth in hardware and software performance. Today, researchers and engi- neers have access to computing power and software that can solve numerical problems which are not fully understood in terms of existing mathemati- cal theory. Thus, computational sciences must in many respects be viewed as experimental disciplines. As a consequence, there is a demand for high- quality, flexible software that allows, and even encourages, experimentation with alternative numerical strategies and mathematical models. Extensibil- ity is then a key issue; the software must provide an efficient environment for incorporation of new methods and models that will be required in fu- ture problem scenarios. The development of such kind of flexible software is a challenging and expensive task. One way to achieve these goals is to in- vest much work in the design and implementation of generic software tools which can be used in a wide range of application fields. In order to provide a forum where researchers could present and discuss their contributions to the described development, an International Work- shop on Modern Software Tools for Scientific Computing was arranged in Oslo, Norway, September 16-18, 1996. This workshop, informally referred to as Sci Tools '96, was a collaboration between SINTEF Applied Mathe- matics and the Departments of Informatics and Mathematics at the Uni- versity of Oslo.

MATLAB Mathematical Analysis is a reference book that presents the techniques of mathematical analysis through examples and exercises resolved with MATLAB software. The purpose is to give you examples of the mathematical analysis functions offered by MATLAB so that you can use them in your daily work regardless of the application. The book supposes proper training in the mathematics and so presents the basic knowledge required to be able to use MATLAB for calculational or symbolic solutions to your problems for a vast amount of MATLAB functions.The book begins by introducing the reader to the use of numbers, operators, variables and functions in the MATLAB environment. Then it delves into working with complex variables. A large section is devoted to working with and developing graphical representations of curves, surfaces and volumes. MATLAB functions allow working with two-dimensional and three-dimensional graphics, statistical graphs, curves and surfaces in explicit, implicit, parametric and polar coordinates. Additional work implements twisted curves, surfaces, meshes, contours, volumes and graphical interpolation.The following part covers limits, functions, continuity and numerical and power series. Then differentiation is addressed in one and several variables including differential theorems for vector fields. Thereafter the topic of integration is handled including improper integrals, definite and indefinite integration, integration in multiple variables and multiple integrals and their applications.Differential equations are exemplified in detail, Laplace transforms, Tayor series, and the Runga-Kutta method and partial differential equations.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.Programming MATLAB for Numerical Analysis introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. You will first become familiar with the MATLAB environment, and then you will begin to harness the power of MATLAB. You will learn the MATLAB language, starting with an introduction to variables, and how to manipulate numbers, vectors, matrices, arrays and character strings. You will learn about MATLAB's high-precision capabilities, and how you can use MATLAB to solve problems, making use of arithmetic, relational and logical operators in combination with the common functions and operations of real and complex analysis and linear algebra. You will learn to implement various numerical methods for optimization, interpolation and solving non-linear equations. You will discover how MATLAB can solve problems in differential and integral calculus, both numerically and symbolically, including techniques for solving ordinary and partial differential equations, and how to graph the solutions in brilliant high resolution. You will then expand your knowledge of the MATLAB language by learning how to use commands which enable you to investigate the convergence of sequences and series, and explore continuity and other analytical features of functions in one and several variables.

This book constitutes the refereed proceedings of the Second International Conference on Algorithmic Decision Theory, ADT 2011, held in Piscataway, NJ, USA, in October 2011.The 24 revised full papers presented were carefully reviewed and selected from 50 submissions.

This book constitutes the refereed proceedings of the 14th International Conference on Information Security, ISC 2011, held in Xi'an, China, in October 2011. The 25 revised full papers were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on attacks; protocols; public-key cryptosystems; network security; software security; system security; database security; privacy; digital signatures.

This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011.The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.

This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011.The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.

The sequencing of the genomes of humans and other organisms is inspiring the developmentofnew statisticalandbioinformatics tools that we hope canmodify the current understanding of human diseases and therapies. As our knowledge about the human genome increases so does our belief that to fully grasp the mechanisms of diseases we need to understand their genetic basis and the p- teomicsbehind them and to integratethe knowledgegeneratedin thelaboratory in clinical settings. The new genetic and proteomic data has brought forth the possibility of developing new targets and therapies based on these ?ndings, of implementing newly developed preventive measures, and also of discovering new research approaches to old problems. To fully enhance our understanding of disease processes, to develop more and better therapies to combat and cure diseases, and to develop strategies to prevent them, there is a need for synergy of the disciplines involved, medicine, molecular biology, biochemistry and computer science, leading to more recent ?elds such as bioinformatics and biomedical informatics. The 6th International Symposium on Biological and Medical Data Analysis aimed to become a place where researchersinvolved in these diversebut incre- ingly complementary areas could meet to present and discuss their scienti?c results. The papers in this volume discuss issues from statistical models to arc- tectures and applications to bioinformatics and biomedicine. They cover both practical experience and novel research ideas and concepts.

The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the area of data mining and knowledge discovery. It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition and automatic scientific discovery, data visualization, causality induction, and knowledge-based systems. This year's conference (PAKDD 2005) was the ninth of the PAKDD series, and carried the tradition in providing high-quality technical programs to facilitate research in knowledge discovery and data mining. It was held in Hanoi, Vietnam at the Melia Hotel, 18-20 May 2005. We are pleased to provide some statistics about PAKDD 2005. This year we received 327 submissions (a 37% increase over PAKDD 2004), which is the highest number of submissions since the first PAKDD in 1997) from 28 countries/regions: Australia (33), Austria (1), Belgium (2), Canada (11), China (91), Switzerland (2), France (9), Finland (1), Germany (5), Hong Kong (11), Indonesia (1), India (2), Italy (2), Japan (21), Korea (51), Malaysia (1), Macau (1), New Zealand (3), Poland (4), Pakistan (1), Portugal (3), Singapore (12), Taiwan (19), Thailand (7), Tunisia (2), UK (5), USA (31), and Vietnam (9). The submitted papers went through a rigorous reviewing process. Each submission was reviewed by at least two reviewers, and most of them by three or four reviewers.

Stata and R are two very flexible data analysis packages. This book details how to extend the power of Stata through the use of R. It steps through more than thirty packages written in both languages, comparing and contrasting their different approaches.