Central Limit Theorem and Related Results

  • Philippe Bougerol
  • Jean Lacroix
Part of the Progress in Probability and Statistics book series (PRPR, volume 8)


In 1970 Kaijser showed in some particular but typical cases that the contractive action of the random products Sn = Yn...Y1 on P(ℝd) implies that Log ∥Snx∥ suitably normalized converges in distribution to a gaussian law (see [38], [39], [40]). This idea was later fully developed by Le Page in [49] where he proved that, loosely speaking, Log ∥Snx∥ behaves like a sum of i.i.d. real random variables and satisfies analogues of the main classical limit theorems. We shall give here a detailed introduction to the important work of Le Page and present, with some improvements, his main results (namely, the central limit theorem with speed of convergence and an estimate of the large deviations of Log ∥Snx∥). We also study the tightness of {Snx, n ≧ 1} without moment assumption. This chapter ends with an application to linear stochastic differential equations.


Probability Measure Lyapunov Exponent Central Limit Theorem Spectral Radius Dirac Measure 
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Copyright information

© Birkhäuser Boston, Inc. 1985

Authors and Affiliations

  • Philippe Bougerol
    • 1
  • Jean Lacroix
    • 2
  1. 1.UER de MathématiquesUniversité Paris 7ParisFrance
  2. 2.Département de MathématiquesUniversité de Paris XIIIVilletaneuseFrance

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