The exponential distribution in information theory books

This article also appears in the life data analysis reference and accelerated life testing data analysis reference books. This book presents the established mathematical techniques that provide the. Most distributions that you have heard of are in the exponential family. If the number of arrivals in a time interval of length t follows a poisson process, then corresponding interarrival time follows an exponential distribution if the interarrival times are independently, identically distributed random variables with an exponential probability distribution, then the number. Information theory needs some measure of variationbut it doesn t have to be h. Blei 1 introduction we discuss the exponential family, a very exible family of distributions. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the.

However, it can practically always be used as a first approximation. Exponential distribution theory and methods request pdf. Uniform distribution maximizes entropy for finite x, hx. The exponential distribution may be viewed as a continuous counterpart of the geometric distribution, which describes the number of bernoulli trials necessary for a discrete process to change state.

Statistical theory department of statistics, university of. This volume provides a systematic and comprehensive synthesis of the diverse lite. The entropy hx of a discrete random variable x with probability distribution. Exponential distribution refers to a statistical distribution used to model the time between independent events that happen at a constant average rate some examples of this distribution are. Estimation in the 2parameter exponential distribution. Maximum entropy probability distribution wikipedia. Basu and a great selection of similar new, used and collectible books available now at great prices. Statistical theory department of statistics, university.

Using an exponential distribution for this type of problem, could be the perfect place where to start. Others have been published in other locations, such as. Basic distributional results and properties asit p. The above interpretation of the exponential is useful in better understanding the properties of the exponential distribution. Exponential distribution an overview sciencedirect topics. The exponential distribution is one of the most significant and widely used distribution in statistical practice. I am working on some practice questions on the exponential distribution and im stuck on this one. Lectures on probability theory and mathematical statistics is an excellent text, because it is clearly written, easily readable, covers a lot of ground, and explains things intuitively.

Characterization problems associated with the exponential. For instance, as we will see, a normal distribution with a known mean is in the one parameter exponential family, while a. This is the sixth book of examples from the theory of probability. The exponential distribution is used to model the behavior of units that. It is the continuous counterpart of the geometric distribution, which is instead discrete. They considered its characterization and properties.

This volume provides a systematic and comprehensive synthesis of the diverse literature on the theory and applications of the exponential distribution. You are allowed to carry the textbook, your own notes and other course related ma terial with. The exponential family in abstract information theory springerlink. Estimating the parameters of a generalized exponential. Part of the lecture notes in computer science book series lncs, volume 8085. Other examples include the length, in minutes, of long distance business telephone calls, and the amount of time, in months, a car. Medhi, in stochastic models in queueing theory second edition, 2003. Mathematically, it is a fairly simple distribution, which many times leads to its use in inappropriate situations.

Information theory communications and signal processing. The above features explain why the exponential distribution is widely used in calculating various systems in queueing theory and reliability theory. Exponential distributions are regulated by a parameter. Estimation in the 2 parameter exponential distribution with prior information abstract. The exponential distribution is an appropriate model where failure of an item is due not to deterioration as a result of wear, but rather to random events. It possesses several important statistical properties, and yet exhibits great mathematical tractability. It is the continuous analogue of the geometric distribution, and it has the key property of. The exponential pdf has no shape parameter, as it has only one shape the exponential pdf is always convex and is stretched to the right as decreases in value the value of the pdf function is always equal to the value of at or the location parameter, if positive, shifts the beginning of the distribution by a distance of to the right of the origin, signifying that the chance failures. Piecewise exponential distribution is also used to bridgeconnect the parametric and nonparametric methodmodel, with the view that when the number of pieces grows to in nite along with the sample size the parametric model becomes the nonparametric model. The primary trait of the exponential distribution is that it is used for modeling the behavior of items with a constant failure rate. It is the constant counterpart of the geometric distribution, which is rather discrete. To see this, think of an exponential random variable in the sense of tossing a lot of coins until observing the first heads.

Exponential distribution definition, formula how to. Theory, methods and applications crc press book the exponential distribution is one of the most significant and widely used distribution in statistical practice. Newest exponentialdistribution questions mathematics. Reference introduced the the maximum likelihood of the unknown parameters for kumaraswamy exponential distribution.

Discussions include exponential regression, models and applications of mixtures, and applications to survival analysis. Exponential distribution ieee conferences, publications. Other chapters consider the exponential dependence of the number of states on. The poisson distribution thus gives an adequate description of the cumulative effect of a large number of events, such that occurrence of an event in a small subinterval is improbable. The exponential distribution occurs naturally when describing the lengths of the interarrival times in a homogeneous poisson processes. It has a fairly simple mathematical form, which makes it fairly easy to manipulate. It possesses due to covid19, orders may be delayed. Jan 22, 2019 the exponential distribution is one of the most significant and widely used distribution in statistical practice. Statistical exponential families of distributions are of great interest both in practice and in theory. Kim, book is published by cambridge university press. We discuss here the maximum likelihood ml method and the method of moments to estimate the parameters. A lot of probabilists and statisticians, as well as actuarial mathematicians, reliability engineers, meteorologists, hydrologists, economists, business and sport analysts, very often deal with order statistics, which plays an important role in various fields of statistics and its applications.

If t k denotes the time interval between the emission of the k. Exponential distribution characteristics reliawiki. In addition, they obtained the information matrix and applied the model to a real data set. It deals in a very particular way with amounts of variation, and with operations which have effect on such amounts. The notion of a sucient statistic is a fundamental one in statistical theory. Ee376a information theory final, monday march 14th 2016.

Exponential distribution formulas, graph, applications. In probability theory and statistics, the exponential distribution is the probability distribution of the time between events in a poisson point process, i. Statisticsdistributionsexponential wikibooks, open. As throughout the course, entropy h and mutual information i are specified in bits. If t is a random variable that represents interarrival times with the exponential distribution, then. Basu and a great selection of similar new, used and collectible books. Introduction to probability models, twelfth edition, is the latest version of sheldon rosss classic bestseller. Lecture notes on information theory department of statistics, yale. The exponential distribution has been successfully applied as a timetofailure model for complex systems consisting of a large number of components in series. Purchase probability and information theory, with applications to radar 2nd.

This volume seeks to provide a systematic synthesis of the literature on the theory and applications of the exponential distribution. Reference introduced the exponentiated kumaraswamy exponential distribution expke. The poisson process and its associated exponential distribution possess many agreeable properties that lead to mathematically tractable results when used in probability models. Statisticsdistributionsexponential wikibooks, open books. Exponential distribution definition and meaning collins.

Exponential distribution definition of exponential. The most important of these properties is that the exponential distribution is memoryless. There are other contexts arising out of extreme value theory as well as information theory that provide justification of using the poisson process in modeling. Other examples include the length, in minutes, of long distance business telephone calls, and the amount of time, in months, a car battery lasts. The exponential distribution is a commonly used distribution in reliability engineering. In addition to the conventional areas, the volume also includes discussions on exponential regression, models and applications of mixtures which includes the especially relevant bootstrapping method, and. It can, however, be used by students of social sciences and mathematicsrelated courses. It is primarily intended for undergraduate students of statistics and mathematics. The authors suggest an approach to studying order statistics which proposes an active participation. In the coming chapters, we show how fisher information measures come to play a central role in sequential universal prediction problems. Abstract information theory information geometry generalized exponential. Exponential distribution is one of the most exploited distributions thanks to its numerous applications in queueing theory, reliability theory, survival analysis etc. Some of these examples also appear in the reference book. This is volume two of the book entitled a first course in probability theory.

Bernoulli, gaussian, multinomial, dirichlet, gamma, poisson, beta 2 setup an exponential family distribution has the following form. It is, in fact, a special case of the weibull distribution where. Nielsen book data summary the exponential distribution is one of the most significant and widely used distributions in statistical practice. The exponential distribution is a probability distribution which represents the time between events in a poisson process. Information theory is defined by concepts and problems. This volume provides a systematic and comprehensive synthesis of the. The terms distribution and family are often used loosely. Exponential distribution encyclopedia of mathematics.

The exponential distribution arises naturally in the study of the poisson distribution introduced in equation. In probability theory and statistics, the exponential distribution a. Relationship between poisson process and exponential. According to the principle of maximum entropy, if nothing is known about a distribution except that it belongs to a certain class usually defined in terms of specified properties or measures, then.

One assumes that the lifetimes of the devices are independent random variables with exponential distributions, and then the property 2 enables one to examine a queueing system by means of finite. Internal report sufpfy9601 stockholm, 11 december 1996 1st revision, 31 october 1998 last modi. It is also called negative exponential distribution. Zipf distribution is related to the zeta distribution, but is. Yes, you can use the exponential distribution to model the time between cars. It is a continuous probability distribution used to represent the time we need to wait before a given event happens. Nov 15, 2016 and the cumulative distribution function is. The notion of entropy, which is fundamental to the whole topic of this book, is introduced. Probability, mathematical statistics, and stochastic processes siegrist 14. Firstly, try to figure out whether the event under consideration is continuous and independent in nature and occurs at a roughly constant rate. Sometimes it is also called negative exponential distribution.

Theory, methods and applications balakrishnan, k basu, asit p download bok. Exponential distribution definition memoryless random. Its importance is also due to the fact that occurrences of events in many reallife. Probability and information theory, with applications to radar 2nd.

In statistics and information theory, a maximum entropy probability distribution has entropy that is at least as great as that of all other members of a specified class of probability distributions. Characterizations of the beta kumaraswamy exponential. In a length of cable, flaws occur with a mean of 0. It possesses several important statistical properties and yet it exhibits great mathematical tractability. For instance, as we will see, a normal distribution with a known mean is in the one parameter exponential family, while a normal distribution with both parameters unknown is in the two parameter exponential family. Semantic scholar extracted view of the exponential distribution in information theory by sergio verdu. The name m stems from the fact that the exponential distribution is the only continuous distribution with the markov property, i. The exponential distribution is a continuous probability distribution used to model the time we need to wait before a given event occurs. Any practical event will ensure that the variable is greater than or equal to zero. It is easy to understand and it is very good for self study as well. This paper proposes a class of estimators for the scale parameter and for the mean of a 2parameter exponential distribution, which is important in life testing and reliability theory, given a. Another common application of exponential distributions is survival analysis eg. Other examples include the length of time, in minutes, of long distance business telephone calls, and the amount of time, in months, a car battery lasts.

Consequently, the ex ponential distribution became basic to research associated with experiments on life expectancy. Exponential families computer science department at. Exponential distribution view this topic in exponential parameters. The exponential distribution in information theory semantic scholar. The exponential distribution theory, methods and applications. Theory, methods and applications 9782884491921 by n. Further research has shown that there are a whole series of problems in reliability theory for which the exponential distribution is inapplicable. For example, the amount of time beginning now until an earthquake occurs has an exponential distribution. Exponential distribution probability density function pdf. This feature of the exponential distribution also implies a constant hazard rate. The distance between one car passing by after the previous one. In the study of continuoustime stochastic processes, the exponential distribution is usually used to model the time until something happens in the process. A threeparameter generalized exponential distribution was suggested by hossain and ahsanullah 5.

240 1584 327 453 797 793 574 1060 1674 1602 46 435 891 1060 765 981 1442 1387 121 1155 707 1088 287 344 1583 532 1333 1078 724 572 1485 125 1168 1081 592 1242 165 1378 403 257 943 1483 1209