標(biāo)題: Titlebook: Applied Probability; Kenneth Lange Textbook 20102nd edition The Editor(s) (if applicable) and The Author(s), under exclusive license to Sp [打印本頁(yè)] 作者: frustrate 時(shí)間: 2025-3-21 17:48
書(shū)目名稱Applied Probability影響因子(影響力)
作者: Gene408 時(shí)間: 2025-3-21 23:17 作者: bioavailability 時(shí)間: 2025-3-22 04:02
Applied Probability978-1-4419-7165-4Series ISSN 1431-875X Series E-ISSN 2197-4136 作者: Uncultured 時(shí)間: 2025-3-22 07:12 作者: 火光在搖曳 時(shí)間: 2025-3-22 11:23 作者: 北極人 時(shí)間: 2025-3-22 16:49 作者: Aboveboard 時(shí)間: 2025-3-22 17:35
Numerical Methods,mmetries supporting exact solutions fade. The current chapter sketches a few of the most promising numerical techniques. Further improvements in computing, statistics, and data management are bound to drive the rapidly growing and disorganized discipline of computational probability for decades to come.作者: 裹住 時(shí)間: 2025-3-22 23:22 作者: encomiast 時(shí)間: 2025-3-23 03:55
Springer Texts in Statisticshttp://image.papertrans.cn/b/image/160062.jpg作者: –DOX 時(shí)間: 2025-3-23 09:02 作者: Aesthete 時(shí)間: 2025-3-23 13:31 作者: 保守 時(shí)間: 2025-3-23 15:01
Urban Green Oases and Recreational Areas,lities, and applied probability. Despite this fact, students seldom see convexity presented in a coherent fashion. It always seems to take a backseat to more pressing topics. The current chapter is intended as a partial remedy to this pedagogical gap.作者: 面包屑 時(shí)間: 2025-3-23 20:57
Urban Green Oases and Recreational Areas,is ill is more exposure, not less. Because combinatorics has so many important applications, serious students of the mathematical sciences neglect it at their peril. Here we explore a few topics in combinatorics that have maximum intersection with probability. Our policy is to assume that readers ha作者: 熱心 時(shí)間: 2025-3-24 00:45
Environmental Concerns and Remediationorithms to solve such problems. Traditionally, these algorithms have been classified by their worst-case performance. Such an analysis can lead to undue pessimism. The average behavior of an algorithm is usually more relevant. Of course, to evaluate the average complexity of an algorithm, we must ha作者: Cpr951 時(shí)間: 2025-3-24 05:44 作者: 縮減了 時(shí)間: 2025-3-24 08:19
Ganesh Chandra Kisku,Pokhraj Sahuastic component [23, 24, 59, 80, 106, 107, 118]. In this chapter we give a few examples and a quick theoretical overview of discrete-time Markov chains. The highlight of our theoretical development, Proposition 7.4.1, relies on a coupling argument. Because coupling is one of the most powerful and in作者: Forsake 時(shí)間: 2025-3-24 14:06
Italian Mediterranean Environment,e useful than discrete-time chains. For one thing, continuous-time chains permit variation in the waiting times for transitions between neighboring states. For another, they avoid the annoyances of periodic behavior. Balanced against these advantages is the disadvantage of a more complex theory invo作者: Genteel 時(shí)間: 2025-3-24 18:53 作者: HEPA-filter 時(shí)間: 2025-3-24 20:08
https://doi.org/10.1007/978-3-540-87963-3strategies to beat the house. Probabilists know better. The real payoff with martingales is their practical value throughout probability theory. This chapter introduces martingales, develops some relevant theory, and delves into a few applications. As a prelude, readers are urged to review the mater作者: 精致 時(shí)間: 2025-3-25 02:30
https://doi.org/10.1007/978-3-540-87963-3n elementary level, stressing intuition rather than rigor. Readers with the time and mathematical inclination should follow up this brief account by delving into serious presentations of the mathematics [80, 107]. A good grounding in measure theory is indispensable in understanding the theory. At th作者: Opponent 時(shí)間: 2025-3-25 04:42 作者: conflate 時(shí)間: 2025-3-25 09:57 作者: 剛毅 時(shí)間: 2025-3-25 14:58 作者: 即席演說(shuō) 時(shí)間: 2025-3-25 17:34 作者: Confirm 時(shí)間: 2025-3-25 23:34 作者: 憤慨點(diǎn)吧 時(shí)間: 2025-3-26 01:08
Basic Notions of Probability Theory, substitute for a previous course in applied probability or for a future course in measure-theoretic probability. Our comments are merely meant as reminders and as a bridge. Many mathematical facts will be stated without proof. This is unsatisfactory, but it is even more unsatisfactory to deny stude作者: 監(jiān)禁 時(shí)間: 2025-3-26 08:03 作者: 起草 時(shí)間: 2025-3-26 11:00 作者: 不能妥協(xié) 時(shí)間: 2025-3-26 15:47
Combinatorics,is ill is more exposure, not less. Because combinatorics has so many important applications, serious students of the mathematical sciences neglect it at their peril. Here we explore a few topics in combinatorics that have maximum intersection with probability. Our policy is to assume that readers ha作者: 使隔離 時(shí)間: 2025-3-26 19:08
Combinatorial Optimization,orithms to solve such problems. Traditionally, these algorithms have been classified by their worst-case performance. Such an analysis can lead to undue pessimism. The average behavior of an algorithm is usually more relevant. Of course, to evaluate the average complexity of an algorithm, we must ha作者: 注意力集中 時(shí)間: 2025-3-27 00:32 作者: Traumatic-Grief 時(shí)間: 2025-3-27 04:14
Discrete-Time Markov Chains,astic component [23, 24, 59, 80, 106, 107, 118]. In this chapter we give a few examples and a quick theoretical overview of discrete-time Markov chains. The highlight of our theoretical development, Proposition 7.4.1, relies on a coupling argument. Because coupling is one of the most powerful and in作者: cartilage 時(shí)間: 2025-3-27 08:57
Continuous-Time Markov Chains,e useful than discrete-time chains. For one thing, continuous-time chains permit variation in the waiting times for transitions between neighboring states. For another, they avoid the annoyances of periodic behavior. Balanced against these advantages is the disadvantage of a more complex theory invo作者: Excise 時(shí)間: 2025-3-27 11:19 作者: Melatonin 時(shí)間: 2025-3-27 16:46
Martingales,strategies to beat the house. Probabilists know better. The real payoff with martingales is their practical value throughout probability theory. This chapter introduces martingales, develops some relevant theory, and delves into a few applications. As a prelude, readers are urged to review the mater作者: NORM 時(shí)間: 2025-3-27 19:35
Diffusion Processes,n elementary level, stressing intuition rather than rigor. Readers with the time and mathematical inclination should follow up this brief account by delving into serious presentations of the mathematics [80, 107]. A good grounding in measure theory is indispensable in understanding the theory. At th作者: 極小量 時(shí)間: 2025-3-28 00:38 作者: 斜 時(shí)間: 2025-3-28 04:31 作者: Arb853 時(shí)間: 2025-3-28 08:45 作者: foppish 時(shí)間: 2025-3-28 13:44
Textbook 20102nd editiond examples from the biological sciences. It can serve as a textbook for graduate students in applied mathematics, biostatistics, computational biology, computer science, physics, and statistics. Readers should have a working knowledge of multivariate calculus, linear algebra, ordinary differential e作者: 貧窮地活 時(shí)間: 2025-3-28 16:41 作者: addition 時(shí)間: 2025-3-28 19:33
Italian Mediterranean Environment,ically and understanding them theoretically then require the matrix exponential function. Kendall’s birth-death-immigration process, treated at the end of the chapter, involves an infinite number of states and transition intensities that depend on time.作者: 迅速飛過(guò) 時(shí)間: 2025-3-29 01:57
Sneha Gautam,Aditya Kumar Patraassical proofs. Our treatment follows the recent trail blazed by Newman [150] and Zagier [211] that uses a minimum of analytic function theory. We particularly stress the connections and insight provided by probability.作者: 易于交談 時(shí)間: 2025-3-29 04:13
Basic Notions of Probability Theory,. As a brief illustration of the material reviewed, we derive properties of the multivariate normal distribution in the final section of this chapter. Later chapters will build on the facts and vocabulary mentioned here and provide more elaborate applications.作者: 背帶 時(shí)間: 2025-3-29 10:28 作者: 格子架 時(shí)間: 2025-3-29 14:02 作者: 防御 時(shí)間: 2025-3-29 19:31 作者: 致命 時(shí)間: 2025-3-29 21:59
https://doi.org/10.1007/978-3-540-87963-3ing theorem, and large deviation bounds via Azuma’s inequality. More extensive treatments of martingale theory appear in the books [23, 24, 53, 80, 106, 118, 208]. Our other referenced sources either provide elementary accounts comparable in difficulty to the current material [129, 170] or interesting special applications [4, 134, 186, 201].作者: Creatinine-Test 時(shí)間: 2025-3-30 01:42
Combinatorics,alan numbers, Stirling numbers of the first and second kind, and the pigeonhole principle. Along the way we meet some applications that we hope will whet readers’ appetites for further study. The books [21, 22, 26, 59, 78, 139, 207] are especially recommended.作者: 圖表證明 時(shí)間: 2025-3-30 06:13
Martingales,ing theorem, and large deviation bounds via Azuma’s inequality. More extensive treatments of martingale theory appear in the books [23, 24, 53, 80, 106, 118, 208]. Our other referenced sources either provide elementary accounts comparable in difficulty to the current material [129, 170] or interesting special applications [4, 134, 186, 201].作者: 遺留之物 時(shí)間: 2025-3-30 09:13 作者: 土產(chǎn) 時(shí)間: 2025-3-30 14:39
Egbert K. Duursma,JoLynn Carrolleady aware of the clever applications of characteristic and moment generating functions. This chapter is intended to review and extend some of the tools that probabilists routinely call on. Readers can consult the books [34, 59, 60, 78, 80, 166] for many additional examples of these tools in action.作者: 組裝 時(shí)間: 2025-3-30 20:33
Land-Use Change as a Disturbance Regime,rocesses stress one-dimensional processes. This is unfortunate because many of the important applications occur in higher dimensions, and the underlying theory is about as simple there. In this chapter, we emphasize multidimensional Poisson processes, their transformation properties, and computational tools for extracting information about them.作者: 凹處 時(shí)間: 2025-3-30 22:35 作者: musicologist 時(shí)間: 2025-3-31 02:19
Calculation of Expectations,eady aware of the clever applications of characteristic and moment generating functions. This chapter is intended to review and extend some of the tools that probabilists routinely call on. Readers can consult the books [34, 59, 60, 78, 80, 166] for many additional examples of these tools in action.作者: 強(qiáng)壯 時(shí)間: 2025-3-31 06:47
Poisson Processes,rocesses stress one-dimensional processes. This is unfortunate because many of the important applications occur in higher dimensions, and the underlying theory is about as simple there. In this chapter, we emphasize multidimensional Poisson processes, their transformation properties, and computational tools for extracting information about them.作者: 有說(shuō)服力 時(shí)間: 2025-3-31 12:45
Branching Processes,spring contributing to the next generation. The key assumption that drives the theory is that particles reproduce independently according to the same probabilistic law. Interactions between particles are forbidden.作者: ANT 時(shí)間: 2025-3-31 14:07
Environmental Concerns and Remediationve some probability model for generating typical problems on which the algorithm operates. The examples in this chapter on sorting, data compression, and graph coloring illustrate some of the underlying models and the powerful techniques probabilists have created for analyzing algorithms.作者: 意見(jiàn)一致 時(shí)間: 2025-3-31 19:03
