What is Random walk: Definition and 96 Discussions

In mathematics, a random walk is a mathematical object, known as a stochastic or random process, that describes a path that consists of a succession of random steps on some mathematical space such as the integers.
An elementary example of a random walk is the random walk on the integer number line,




Z



{\displaystyle \mathbb {Z} }
, which starts at 0 and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in a liquid or a gas (see Brownian motion), the search path of a foraging animal, the price of a fluctuating stock and the financial status of a gambler: all can be approximated by random walk models, even though they may not be truly random in reality.
As illustrated by those examples, random walks have applications to engineering and many scientific fields including ecology, psychology, computer science, physics, chemistry, biology, economics, and sociology. Random walks explain the observed behaviors of many processes in these fields, and thus serve as a fundamental model for the recorded stochastic activity. As a more mathematical application, the value of π can be approximated by the use of a random walk in an agent-based modeling environment. The term random walk was first introduced by Karl Pearson in 1905.Various types of random walks are of interest, which can differ in several ways. The term itself most often refers to a special category of Markov chains, but many time-dependent processes are referred to as random walks, with a modifier indicating their specific properties. Random walks (Markov or not) can also take place on a variety of spaces: commonly studied ones include graphs, others on the integers or the real line, in the plane or higher-dimensional vector spaces, on curved surfaces or higher-dimensional Riemannian manifolds, and also on groups finite, finitely generated or Lie. The time parameter can also be manipulated. In the simplest context the walk is in discrete time, that is a sequence of random variables (Xt) = (X1, X2, ...) indexed by the natural numbers. However, it is also possible to define random walks which take their steps at random times, and in that case, the position Xt has to be defined for all times t ∈ [0,+∞). Specific cases or limits of random walks include the Lévy flight and diffusion models such as Brownian motion.
Random walks are a fundamental topic in discussions of Markov processes. Their mathematical study has been extensive. Several properties, including dispersal distributions, first-passage or hitting times, encounter rates, recurrence or transience, have been introduced to quantify their behavior.

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  1. J

    I Can anyone explain me this quantum entanglement experiment

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  2. K

    I Exploring Continuous Approximation of 1D Random Walk Steps (Reif, pg 14)

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  3. G

    Fortran Solving Magnetic Field Using Floating Random Walk

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  4. J

    I How to choose a random walk to best model diffusion?

    To choose random walk on a graph, it seems natural to to assume that the walker jumps using each possible edge with the same probability (1/degree) - such GRW (generic random walk) maximizes entropy locally (for each step). Discretizing continuous space and taking infinitesimal limit we get...
  5. dRic2

    Calculating the Probability of Two Men Meeting Again with a Double Random Walk

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  6. H

    Unit of Velocity from a Random Walk measured by an accelerometer

    Hi, I am working on a kalman filter where my measurement equation involves "-g + v" , where g is in m/s^2 and v is velocity random walk given in m/s/sqrt(hr). Feels like a stupid question, but how can I transform the unit of velocity random walk so I can do the calculation correctly?
  7. C

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  8. arcTomato

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  9. arcTomato

    Please teach me how to prove this random walk problem....

    I think I can prove equal length version problem, But I am confusing in this case,,, Please help me!
  10. iVenky

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  11. Kitty123

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  12. G

    A How can I simulate 2D correlated data with continuous-valued variables?

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  13. G

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  14. B

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  15. J

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  16. S

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  17. grquanti

    I Jump probability of a random walker

    Hello everybody. I have a Markowian homogeneous random walk. Given the transition matrix of the chain, I know that ##P[ X(t) = i | X(t-1) = j ] ≡ P_{j→i}=T_{ij}## where ##T## is the transition matrix and ##X(t)## is the position of the walker...
  18. P

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    Hi, I have the following homework question: Let Xt be the continuous-time simple random walk on a circle as in Example 2, Section 7.2. Show that there exists a c,β > 0, independent of N such that for all initial probability distributions ν and all t > 0 ∥νe^tA−π∥_TV ≤ ce^(−βt/N2) Here's what...
  19. F

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  20. J

    I Average number of times a random walk passes a point

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  21. Themis

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  22. S

    Can someone retrace this easy random walk calculation?

    Okay, it's not easy for me but probably for you ;) Hello first of all! I have two questions: 1. Why is there a minus before the expression in the red circle? 2. How did the x((n-1)-1) in the last line come to be?More precise: I understand the first parts. It's the random walk and x signifies...
  23. S

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    Hello! I'm struggling with a probably easy physics question concerning random walks. Here I have the slide regarding this: Delta is the distance that a particle moves. Can someone explain where the n-1 initially comes from? Does it have to do wtih the concept of the degrees of freedom? Than...
  24. Buzz Bloom

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    I have been puzzled about the possible interaction mechanisms among the various particles during inflation that would have performed the mixing of mass-energy (ME) required for the uniformity of the CBR. Here is my understanding about what must happen to acheve the necessary mixing of ME during...
  25. jk22

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  26. H

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  27. M

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  28. Rapier

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  29. K

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  30. C

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  31. B

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  32. A

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  34. L

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  35. M

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  36. M

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  37. S

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  38. P

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  39. S

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  40. W

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  41. R

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  42. C

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  43. F

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  44. H

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  46. P

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  47. M

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  48. P

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  49. J

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  50. S

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