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"Tugas akhir ini secara umum bertujuan untuk menghadirkan suatu metode yang dapat membantu kita dalam menghitung nilai-nilai probabilitas transisi yang dibutuhkan dalam penghitungan aktuaria. Penghitungan nilai-nilai probabilitas transisi ini dibatasi pada model tiga state. Pembahasan model ini berkaitan erat dengan proses Markov dan menggunakan nilai force of transition konstan (Proses Markov waktu homogen). Metode yang digunakan dalam mencari nilai-nilai probabilitas transisi berangkat dari penggunaan matriks force of transition dengan force of transition yang bernilai konstan yaitu persamaan P(t) = Adiag( ed1t ,ed2t ,ed3t )A?1 dimana elemen-elemen matriks P(t) ialah nilai probabilitas transisi, vektor kolom dari matriks A ialah vektor eigen dari matriks force of transition, dan nilai d1, d2, d3 ialah nilai-nilai eigen dari matriks force of transition. Proses penghitungan nilai-nilai probabilitas ini melalui pencarian nilai eigen dan vektor eigen dari matriks force of transition. Dalam kasus khusus pada model khusus tiga state,yaitu state select, ultimate, dan dead, akan dibahas perhitungan numerik untuk mencari nilai-nilai probabilitas transisinya."

""This book offers a practical, concise introduction to regression analysis for upper-level undergraduate students of diverse disciplines including, but not limited to statistics, the social and behavioral sciences, MBA, and vocational studies. The book’s overall approach is strongly based on an abundant use of illustrations, examples, case studies, and graphics. It emphasizes major statistical software packages, including SPSS(r), Minitab(r), SAS(r), R, and R/S-PLUS(r). Detailed instructions for use of these packages, as well as for Microsoft Office Excel(r), are provided on a specially prepared and maintained author web site. Select software output appears throughout the text. To help readers understand, analyze, and interpret data and make informed decisions in uncertain settings, many of the examples and problems use real-life situations and settings. The book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series and forecasting. New to this edition are more exercises, simplification of tedious topics (such as checking regression assumptions and model building), elimination of repetition, and inclusion of additional topics (such as variable selection methods, further regression diagnostic tests, and autocorrelation tests)"-- Provided by publisher."

"This monograph is a presentation of a unified approach to a certain class of semimartingale inequalities, which can be regarded as probabilistic extensions of classical estimates for conjugate harmonic functions on the unit disc. The approach, which has its roots in the seminal works of Burkholder in the 80s, enables to deduce a given inequality for semimartingales from the existence of a certain special function with some convex-type properties. Remarkably, an appropriate application of the method leads to the sharp version of the estimate under investigation, which is particularly important for applications. These include the theory of quasiregular mappings (with deep implications to the geometric function theory), the boundedness of two-dimensional Hilbert transform and a more general class of Fourier multipliers, the theory of rank-one convex and quasiconvex functions, and more. The book is divided into a few separate parts. In the introductory chapter present motivation for the results and relate them to some classical problems in harmonic analysis. The next part contains a general description of the method, which is applied in subsequent chapters to the study of sharp estimates for discrete-time martingales, discrete-time sub- and supermartingales, continuous time processes, the square and maximal functions. Each chapter contains additional bibliographical notes included for reference.​ "

"This volume collects twenty articles on various topics in this field, including self-interacting random walks and polymer models in random and non-random environments, branching processes, Parisi formulas and metastability in spin glasses, and hydrodynamic limits for gradient Gibbs models. The majority of these articles contain original results at the forefront of contemporary research, some of them include review aspects and summarize the state-of-the-art on topical issues, one focal point is the parabolic Anderson model, which is considered with various novel aspects including moving catalysts, acceleration and deceleration and fron propagation, for both time-dependent and time-independent potentials. "

"This book establishes the theory of how to go about estimating not just scalar parameters about a proposed model, but also the underlying structure of the model itself. Classic statistical tools are used, the law of large numbers, and the central limit theorem. Researchers have recently developed creative and original methods to use these tools in sophisticated (but highly technical) ways to reveal new details about the underlying structure. This book will be of special interest to researchers, combining the theory of mathematical finance with its investigation using market data, and it will also prove to be useful in a broad range of applications, such as to mathematical biology, chemical engineering, and physics. "

"This book is covers Markov chains in discrete and continuous time, poisson processes, renewal processes, martingales, and mathematical finance. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. There are many new examples and problems with solutions that use the TI-83. Some material that was too advanced for the level has been eliminated while the treatment of other topics useful for applications has been expanded. In addition, the ordering of topics has been improved. For example, the difficult subject of martingales is delayed until its usefulness can be seen in the treatment of mathematical finance. "

"Distribusi Transmuted Exponentiated Exponential merupakan generalisasi dari distribusi Exponentiated Exponential yang dibentuk dengan menggunakan metode quadratic rank transmutation maps (QRTM). Distribusi Transmuted Exponentiated Exponential merupakan salah satu distribusi kontinu yang mampu memodelkan data dengan hazard rate naik, turun, bathtub, dan non-monoton. Pada tugas akhir ini akan dibahas konstruksi dari distribusi Transmuted Exponentiated Exponential. Karakteristik-karakteristik distribusi yang meliputi fungsi kepadatan probabilitas, fungsi distribusi, dan hazard rate dari distribusi Transmuted Exponentiated Exponential juga dijelaskan lebih lanjut. Pada bagian akhir, diberikan suatu aplikasi dari distribusi Transmuted Exponentiated Exponential pada suatu data lifetime.

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Transmuted Exponentiated Exponential distribution is a generalization of Exponentiated Exponential distribution which formed using a method called quadratic rank transmutation maps (QRTM). Transmuted Exponentiated Exponential distribution is a continued distribution which can model increasing, decreasing, bathtub, and non-monotone hazard rate. In this paper, it will be explained how to form Transmuted Exponentiated Exponential distribution. Characteristics of distribution such as, probability density function, distribution function, and hazard rate of Transmuted Exponentiated Exponential distribution will be explained further. Finally, a set of lifetime data will be analyzed using Transmuted Exponentiated Exponential distribution as an illustration."

"Metode Tomografi Probabilitas merupakan suatu konsep bare dalam upaya mengetahui kebolehjadian suatu unit sel benda memiliki parameter fisis tertentu, yang didefinisikan sebagai sebuah besaran fisis yang berhubungan secara linear dengan respon yang ditimbulkannya. Pengukuran besaran fisis tersebut secara langsung memiliki beberapa hambatan baik hambatan teknis maupun hambatan ekonomis, sehingga dipakai teknik pengukuran tomografi. Konsep tomografi akan diterapkan pada interpretasi data tahanan jenis semu dua dimensi yang diukur semi-tomografi di permukaan medium sintetis dengan konfigurasi dipole-dipole. Data keluaran basil pemrosesan adalah kebolehj adi-an sel-sel pada suatu grid model yang memiliki nilai tahanan jenis tertentu. Secara visual, kontur probabilitas dapat menggambarkan keberadaan anomali yang memiliki tahanan jenis lebih besar ataupun lebih kecil dari tahanan jenis baku yang ditentukan. Metode dan perangkat lunak tomografi probabilitas yang dibuat, diujicobakan dengan model-model sintetis yang cukup bervariatif dan menghasilkan bentukan anomali yang relatif sama dengan model yang digunakan. "