Computational Probability: Algorithms and Applications in the Mathematical SciencesSpringer Science & Business Media, 2008. gada 8. janv. - 222 lappuses Computational probability encompasses data structures and algorithms that have emerged over the past decade that allow researchers and students to focus on a new class of stochastic problems. COMPUTATIONAL PROBABILITY is the first book that examines and presents these computational methods in a systematic manner. The techniques described here address problems that require exact probability calculations, many of which have been considered intractable in the past. The first chapter introduces computational probability analysis, followed by a chapter on the Maple computer algebra system. The third chapter begins the description of APPL, the probability modeling language created by the authors. The book ends with three applications-based chapters that emphasize applications in survival analysis and stochastic simulation. The algorithmic material associated with continuous random variables is presented separately from the material for discrete random variables. Four sample algorithms, which are implemented in APPL, are presented in detail: transformations of continuous random variables, products of independent continuous random variables, sums of independent discrete random variables, and order statistics drawn from discrete populations. The APPL computational modeling language gives the field of probability a strong software resource to use for non-trivial problems and is available at no cost from the authors. APPL is currently being used in applications as wide-ranging as electric power revenue forecasting, analyzing cortical spike trains, and studying the supersonic expansion of hydrogen molecules. Requests for the software have come from fields as diverse as market research, pathology, neurophysiology, statistics, engineering, psychology, physics, medicine, and chemistry. |
No grāmatas satura
1.–5. rezultāts no 23.
... plots. But pity the poor probabilist, who through all those es had only paper and pencil for symbolic calculations. The purpose s monograph is to address the plight of the probabilist by providing alms to perform calculations associated ...
... plot the PDF of V = XY. he APPL code to solve this problem is: = Triangular RW (1, 2, 4); TriangularRW (1, 2, 3); := Product (X, Y); > PlotDist (W); : - 0.1 0 2 x 0.3 12 8 6 4 0.4. hich returns the PDF Of V as –#v + #ln v + # In v + # 1 ...
... plot (power, theta = 0 . . 20); he power function is shown in Figure 1.2. Obviously, this example 0.8 0.6 0.4 0.2 0 theta~20 15 10 5 0. in ha o an aralizarl far a liffarant canniala cirzac nannila +ian alie+ril→ 11+iane returns the PDF ...
... plotting, and programming, just to name a few of the basics. is, simply, a set of supplementary Maple commands and procedures ugments the existing computer algebra system. In effect, APPL takes apabilities of Maple and turns it into a ...
... plots, can be given a name, but it is indeed helpful to choose he that describes the expression. The restart command makes Maple lmost) as if it has just been started, and it clears the values of all Maple les. Some guidelines for ...
Saturs
6 | |
Solving Equations | 20 |
Simple Algorithms | 37 |
Examples | 50 |
roducts of Random Variables | 55 |
ata Structures and Simple Algorithms | 71 |
ums of Independent Random Variables | 92 |
Algorithm | 106 |
rder Statistics | 119 |
teliability and Survival Analysis 135 | 133 |
to chastic Simulation 153 | 152 |
ther Applications | 185 |
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Computational Probability: Algorithms and Applications in the Mathematical ... John H. Drew,Diane L. Evans,Andrew G. Glen,Lawrence Leemis Priekšskatījums nav pieejams - 2007 |
Computational Probability: Algorithms and Applications in the Mathematical ... John H. Drew,Diane L. Evans,Andrew G. Glen,Lawrence Leemis Priekšskatījums nav pieejams - 2010 |