Probability stochastic process (79 résultats)

Hardcover. Etat : Good. 2nd edition. Light wear to boards. Content is clean with light toning. Good DJ with little wear and toning.

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Etat : New. 1st ed. 2020 edition NO-PA16APR2015-KAP.

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paperback. Etat : New. Ship out in 2 business day, And Fast shipping, Free Tracking number will be provided after the shipment.Paperback. Pub Date: Unknown Language: Chinese Publisher: Beijing University of Posts and Telecommunications Press Limited Basic information Title : Probability theory and mathematical statistics random process Price: 28.00 yuan Author: Publisher : Beijing University of Posts and Telecommunications Press Limited Publication Date : ISBN: 9787563508570 words: Page: Revision: Binding: Size: weight : Editor's Summary catalog preface the author introduces DigestFour Satisfaction guaranteed,or money back.…

paperback. Etat : New. Paperback.Pub Date:2021-01-01 Pages:303 Language:Chinese Publisher:Beijing University of Posts and Telecommunications Press Probability Theory and Stochastic Process is compiled according to the needs of engineering multi-level teaching reform and years of teaching practice. mainly including Probability theory and stochastic process are two parts. The probability theory part includes: the basic concepts of probability theory. random variables and their distribution. multi-dimensional random v. …

paperback. Etat : New. Language:Chinese.Introduction to Applied stochastic process probability model (English 11th Edition).

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! Ruin theory, sometimes referred to as collective risk theory, is a branch of actuarial science that studies an insurer's vulnerability to insolvency based on mathematical modeling of the insurer's surplus. The theory permits the derivation and calculation of many ruin-related measures and quantities, including the probability of ultimate ruin, the distribution of an insurer's surplus immediately prior to ruin, the deficit at the time of ruin, the distribution of the first drop in surplus given that the drop occurs, etc. It is also considered as an area of applied probability because most of the techniques and methodologies adopted in ruin theory are based on the application of stochastic processes. Though most problems in ruin theory stem from real-life actuarial studies, it is the mathematical aspects of ruin theory that have drawn much of the attention from actuarial scientists and probabilists in the past few decades.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! A utilization distribution is a probability distribution constructed from data providing the location of an individual in space at different points in time. In probability theory and statistics, a probability distribution identifies either the probability of each value of an unidentified random variable when the variable is discrete, or the probability of the value falling within a particular interval when the variable is continuous. The probability distribution describes the range of possible values that a random variable can attain and the probability that the value of the random variable is within any subset of that range.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online.In probability theory, a stochastic process, or sometimes random process, is the counterpart to a deterministic process. Instead of dealing with only one possible 'reality' of how the process might evolve under time (as is the case, for example, for solutions of an ordinary differential equation), in a stochastic or random process there is some indeterminacy in its future evolution described by probability distributions. This means that even if the initial condition (or starting point) is known, there are many possibilities the process might go to, but some paths are more probable and others less.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! A phase-type distribution is a probability distribution that results from a system of one or more inter-related Poisson processes occurring in sequence, or phases. The sequence in which each of the phases occur may itself be a stochastic process. The distribution can be represented by a random variable describing the time until absorption of a Markov process with one absorbing state. Each of the states of the Markov process represents one of the phases.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. An ( ,d, )-superprocess, X(t,dx), is a stochastic process on mathbb{R} imes mathbb{R}^d that is usually constructed as a special limit of branching diffusion where the branching mechanism is given by its factorial moment generating function: Phi(s) = frac{1}{1+beta}(1-s)^{1+beta}+s and the spatial motion of individual particles is given by the -symmetric stable process with infinitesimal generator .The = 2 case corresponds to standard Brownian motion and the (2,d,1)-superprocess is called the Dawson-Watanabe superprocess or super-Brownian motion.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In the theory of stochastic processes, a part of the mathematical theory of probability, the variance gamma process (VG), also known as Laplace motion, is a Lévy process determined by a random time change. The process has finite moments distinguishing it from many Lévy processes. There is no diffusion component in the VG process and it is thus a pure jump Lévy process. The increments are independent and follow a Laplace distribution. There are several representations of the VG process that relate it to other processes. It can for example be written as a Brownian motion subjected to a random time change following a gamma process. Since the VG process is of finite variation it can be written as the difference of two independent gamma processes. Alternatively it can be approximated by a compound Poisson process that leads to a representation with explicitly given (independent) jumps and their locations. This last characterization gives an understanding of the strucuture of the sample path with location and sizes of jumps.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In the mathematical sciences, a stationary process (or strict(ly) stationary process or strong(ly) stationary process) is a stochastic process whose joint probability distribution does not change when shifted in time or space. As a result, parameters such as the mean and variance, if they exist, also do not change over time or position. Stationarity is used as a tool in time series analysis, where the raw data are often transformed to become stationary, for example, economic data are often seasonal and/or dependent on the price level. Processes are described as trend stationary if they are a linear combination of a stationary process and one or more processes exhibiting a trend. Transforming these data to leave a stationary data set for analysis is referred to as de-trending.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In the mathematical sciences, a stationary process (or strict(ly) stationary process or strong(ly) stationary process) is a stochastic process whose joint probability distribution does not change when shifted in time or space. As a result, parameters such as the mean and variance, if they exist, also do not change over time or position. Stationarity is used as a tool in time series analysis, where the raw data are often transformed to become stationary, for example, economic data are often seasonal and/or dependent on the price level. Processes are described as trend stationary if they are a linear combination of a stationary process and one or more processes exhibiting a trend. Transforming these data to leave a stationary data set for analysis is referred to as de-trending.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In probability theory, the telegraph process is a memoryless continuous-time stochastic process that shows two distinct values. If these are called a and b, the process can be described by the following master equations: partial_t P(a, t x, t_0)=-lambda P(a, t x, t_0)+mu P(b, t x, t_0) and partial_t P(b, t x, t_0)=lambda P(a, t x, t_0)-mu P(b, t x, t_0). The process is also known under the names Katz process, dichotomous random process.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! Ruin theory, sometimes referred to as collective risk theory, is a branch of actuarial science that studies an insurer's vulnerability to insolvency based on mathematical modeling of the insurer's surplus. The theory permits the derivation and calculation of many ruin-related measures and quantities, including the probability of ultimate ruin, the distribution of an insurer's surplus immediately prior to ruin, the deficit at the time of ruin, the distribution of the first drop in surplus given that the drop occurs, etc. It is also considered as an area of applied probability because most of the techniques and methodologies adopted in ruin theory are based on the application of stochastic processes. Though most problems in ruin theory stem from real-life actuarial studies, it is the mathematical aspects of ruin theory that have drawn much of the attention from actuarial scientists and probabilists in the past few decades.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In probability theory and statistics, the Gumbel distribution (named after Emil Julius Gumbel (1891 1966)) is used to model the distribution of the maximum (or the minimum) of a number of samples of various distributions. For example we would use it to represent the distribution of the maximum level of a river in a particular year if we had the list of maximum values for the past ten years. It is useful in predicting the chance that an extreme earthquake, flood or other natural disaster will occur.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! The Watts and Strogatz model is a random graph generation model that produces graphs with small-world properties, including short average path lengths and high clustering. It was proposed by Duncan J. Watts and Steven Strogatz in their joint 1998 Nature paper. The model also became known as the Watts beta model after Watts used to formulate it in his popular science book Six Degrees. The formal study of random graphs dates back to the work of Paul Erd s and Alfréd Rényi. The graphs they considered, now known as the classical or Erd s Rényi graphs, offer a simple and powerful model with many applications.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In probability theory and statistics, the discrete uniform distribution is a discrete probability distribution that can be characterized by saying that all values of a finite set of possible values are equally probable. In case the values of a random variable with a discrete uniform distribution are real, it is possible to express the cumulative distribution function in terms of the degenerate distribution.…

Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In probability theory specifically in the theory of stochastic processes, a stationary sequence is a random sequence whose joint probability distribution is invariant over time.Probability theory is the branch of mathematics concerned with analysis of random phenomena. The central objects of probability theory are random variables, stochastic processes, and events: mathematical abstractions of non-deterministic events or measured quantities that may either be single occurrences or evolve over time in an apparently random fashion. Although an individual coin toss or the roll of a die is a random event, if repeated many times the sequence of random events will exhibit certain statistical patterns, which can be studied and predicted. Two representative mathematical results describing such patterns are the law of large numbers and the central limit theorem.…