Skip to main content
Log in

Weighted laws of large numbers and convergence of weighted ergodic averages on vector valued \(L_p\)-spaces

  • Original Paper
  • Published:
Advances in Operator Theory Aims and scope Submit manuscript

Abstract

A more general notion of weight called admissible is introduced and then an investigation is carried out on the a.e. convergence of weighted strong laws of large numbers and their applications to weighted ergodic averages on vector-valued \(L_p\)-spaces.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Aistleitner, C.: Convergence of $\sum c_kf(kx)$ and the Lip $\alpha $ class. Proc. Am. Math. Soc. 140, 3893–3903 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  2. Akhmedov, A., Comez, D.: Good modulating sequences for the ergodic Hilbert transform. Turk. J. Math. 39, 124–138 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  3. Assani, I.: Strong laws for weighted sums of independent identically distributed random variables. Duke Math. J. 88, 217–246 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  4. Assani, I.: A weighted pointwise ergodic theorem. Ann. Inst. H. Poincare Probab. Stat. 34, 139–150 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  5. Assani, I., Lin, M.: On the one-sided Hilbert transform. Contemp. Math. 430, 21–39 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  6. Baum, L., Katz, M.: Convergence rates in the law of large numbers. Trans. Am. Math. Soc. 120, 108–123 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  7. Berend, D., Lin, M., Rosenblatt, J., Tempelman, A.: Modulated and subsequential ergodic theorems in Hilbert and Banach spaces. Ergod. Theory Dyn. Syst. 22, 1653–1665 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  8. Berkes, I., Weber, M.: On series $\sum c_kf(n_kx)$. Mem. Am. Math. Soc. 201(943) (2009), 72 p.

  9. Bernardis, A.L., Martin-Reyes, F.J., Gavilvan, M.D.S.: The ergodic Hilbert transform in the Cesro-$\alpha $ sense for invertible Lamperti operators. Q. J. Math. Oxf. Ser. 50, 389–399 (1999)

    Article  MATH  Google Scholar 

  10. Boukhari, F., Malti, D.: Convergence of series of strongly integrable random variables and applications. Stat. Probab. Lett. 137, 191–200 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  11. Boukhari, F., Weber, M.: Almost sure convergence of weighted series of contractions. Ill. J. Math. 46, 1–21 (2002)

    MathSciNet  Google Scholar 

  12. Chevallier, N., Cohen, G., Conze, J.-P.: On the convergence of the rotated one-sided ergodic Hilbert transform. Positivity 15, 253–270 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  13. Cohen, G., Lin, M.: Laws of large numbers with rates and the one-sided ergodic Hilbert transform. Ill. J. Math. 47, 997–1031 (2003)

    MathSciNet  MATH  Google Scholar 

  14. Cohen, G., Lin, M.: Extensions of the Menchoff–Rademacher theorem with applications to ergodic theory. Isr. J. Math. 148, 41–86 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Cohen, G., Lin, M.: The one-sided ergodic Hilbert transform of normal contractions. In book: D. Alpay, V. Vinnikov (Eds), Characteristic Functions. Scattering Functions and Transfer Functions, pp. 77–98. Birkhauser, Basel (2009)

  16. Cohen, G., Cuny, C., Lin, M.: The one-sided ergodic Hilbert transform in Banach spaces. Stud. Math. 196, 251–263 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  17. Comez, D.: The ergodic Hilbert transform for admissible processes. Can. Math. Bull. 49, 203–212 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  18. Cotlar, M.: A unified theory of Hilbert transforms and ergodic theorems. Rev. Mat. Cuyana 1, 105–167 (1955)

    MathSciNet  Google Scholar 

  19. Cuny, C.: On the a.s. convergence of the one-sided ergodic Hilbert transform. Ergod. Theory Dyn. Syst. 29, 1781–1788 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  20. Cuny, C.: Almost everywhere convergence of generalized ergodic transforms for invertible power-bounded operators in $L_p$. Colloq. Math. 124, 61–77 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  21. Darwiche, A., Schneider, D.: Convergence of weighted ergodic averages. arXiv:2007.01119

  22. Derriennic, Y., Lin, M.: Fractional Poisson equations and ergodic theorems for fractional coboundaries. Isr. J. Math. 123, 93–130 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  23. Diestel, J., Uhl, J.J.: Vector Measures. Mathematical Surveys and Monographs. American Mathematical Society, Providence (1977)

    Google Scholar 

  24. Dunford, N., Schwartz, J.T.: Linear Operators I. General Theory. Interscience Publishers, New York (1964)

    MATH  Google Scholar 

  25. Durand, F., Schneider, D.: Ergodic averages with deterministic weights. Ann. Inst. Fourier 52, 561–583 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  26. Etemadi, N.: Stability of sums of weighted nonnegative random variables. J. Multivar. Anal. 13, 361–365 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  27. Fan, A.H.: Almost everywhere convergence of ergodic series. Ergod. Theory Dyn. Syst. 37, 490–511 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  28. Fan, A.H.: Weighted Birkhoff ergodic theorem with oscillating weights. Ergod. Theory Dyn. Syst. 39, 1275–1289 (2019)

    Article  MathSciNet  Google Scholar 

  29. Gaposhkin, V.: On the dependence of the convergence rate in the SLLN for stationary processes on the rate of decay of the correlation function. Theory Probab. Appl. 26, 706–720 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  30. Gaposhkin, V.: Spectral criteria for existence of generalized ergodic transforms. Theory Probab. Appl. 41, 247–264 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  31. Halmos, P.: A nonhomogeneous ergodic theorem. Trans. Am. Math. Soc. 66, 284–288 (1949)

    MathSciNet  MATH  Google Scholar 

  32. Jamison, B., Orey, S., Pruitt, W.: Convergence of weighted averages of independent random variables. Z. Wahrscheinlichkeitstheorie Verw. Geb. 4, 40–44 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  33. Krengel, U.: Ergodic Theorems. de Gruyter, Berlin (1985)

    Book  MATH  Google Scholar 

  34. Lesigne, E.: Un theoreme de disjonction de systémes dynamiques et une generalisation du theoreme ergodique de Wiener–Wintner. Ergod. Theory Dyn. Syst. 10, 513–521 (1990)

    Article  MATH  Google Scholar 

  35. Lin, M., Weber, M.: Weighted ergodic theorems and strong laws of large numbers. Ergod. Theory Dyn. Syst. 27, 511–543 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  36. Lin, M., Olsen, J., Tempelman, A.: On modulated ergodic theorems for Dunford–Schwartz operators. Ill. J. Math. 43, 542–567 (1999)

    MathSciNet  MATH  Google Scholar 

  37. Marcus, M.B., Piseer, G.: Random Fourier Series with Applications to Harmonic Analysis, Ann. Math. Studies. Princeton University Press, Princeton (1981)

    Google Scholar 

  38. Moricz, F.: Moment inequalities and the strong laws of large numbers. Z. Wahrscheinlichkeitstheorie Verw. Geb. 35, 299–314 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  39. Moricz, F., Tandori, K.: Almost everywhere convergence of orthogonal series revisited. J. Math. Anal. Appl. 182, 637–653 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  40. Mukhamedov, F., Rafeiro, H.: Weighted strong laws of large numbers on vector-valued variable exponent Lebesgue spaces. Rend. Lincei Mat. Appl. 31(4), 791–814 (2020)

    MathSciNet  MATH  Google Scholar 

  41. Peskir, G., Schneider, D., Weber, M.: Randomly weighted series of contractions in Hilbert spaces. Math. Scand. 79, 263–282 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  42. Riesz, F., Sz.-Nagy, B.: Lecons d’analyse fonctionnelle. Akademiai Kiado, Budapest (1955)

    MATH  Google Scholar 

  43. Rosenblatt, J.: Almost everywhere convergence of series. Math. Ann. 280, 565–577 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  44. Weber, M.: Estimating random polynomials by means of metric entropy methods. Math. Inequal. Appl. 3, 443–457 (2000)

    MathSciNet  MATH  Google Scholar 

  45. Zygmund, A.: Trigonometric Series, 2nd edn. Cambridge University Press, Cambridge (1968)

    MATH  Google Scholar 

Download references

Acknowledgements

The author thanks the UAEU UPAR Grant No. G00003247 (Fund. 31S391) for support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Farrukh Mukhamedov.

Additional information

Communicated by Timur Oikhberg.

Appendices

Appendix A: Examples of admissible weighted

In this section, we provide some examples of admissible weights (see [40]).

Example A.1

Let \(G_n=n^{1-\beta }\), for some \(\beta \in (0,1]\) and \(p>1\). Define a weight \(\{W_n\}\) by \(W_n=n^{1-\delta }\) with \(\delta \in [0,\frac{p-1}{p}\beta )\). Let us set \(n_k=[k^r]+1\), where \(r=1/\beta\). Then, \(\{W_n\}\) is \((p,\{n_k\})\)-admissible. Indeed, one has

$$\begin{aligned} \sum _{k=1}^\infty \left( \frac{G_{n_k}}{W_{n_k}}\right) ^p&= {} \sum _{k=1}^\infty \frac{1}{n_k^{(\beta -\delta )p}}\\ &\le {} \sum _{k=1}^\infty \frac{1}{k^{pr(\beta -\delta )}}<\infty \end{aligned}$$

since \(pr(\beta -\delta )=(1-r\delta )p>1\). Hence, the condition (2.1) is satisfied. Let us check (2.2). From the definition of the sequences, one gets

$$\begin{aligned} \frac{n_{k+1}-n_k}{W_{n_k}}&\le {} \frac{(k+1)^r+1-k^r}{(k^r)^{1-\delta }} \\ &\le {} \frac{2r(k+2)^{r-1}}{k^{r(1-\delta )}} \\&= {} 2r\left( \frac{k+2}{k}\right) ^{r-1}\frac{1}{k^{1-r\delta }} \end{aligned}$$
(A.1)

Hence,

$$\begin{aligned} \left( \frac{n_{k+1}-n_k}{W_{n_k}}\right) ^p\le (2r)^p\left( \frac{k+2}{k}\right) ^{p(r-1)}\frac{1}{k^{p(1-r\delta )}} \end{aligned}$$
(A.2)

which, due to the choice of \(\delta\), implies (2.2). We point out that this kind of weight was considered in [13]

Example A.2

Let \({{\tilde{G}}}_n=n^{1-\beta }\ln ^\gamma n\), for some \(\beta \in (0,1]\), \(\gamma \ge 1\) and \(p>1\). Then a weight given by \({{\tilde{W}}}_n=n^{1-\delta }\ln ^\gamma n\) with \(\delta \in [0,\frac{p-1}{p}\beta )\) is \((p,\{n_k\})\)-admissible w.r.t. \(\{{{\tilde{G}}}_n\}\), here as before, \(n_k=[k^r]+1\), where \(r=1/\beta\). Using the same argument as in Example A.1, we easily obtain (2.1). Now according to (A.2), one finds

$$\begin{aligned} \left( \frac{n_{k+1}-n_k}{{{\tilde{W}}}_{n_k}}\right) ^p &\le {} (2r)^p\left( \frac{k+2}{k}\right) ^{p(r-1)}\frac{1}{k^{p(1-r\delta )}\ln ^{\gamma p} k}\\ &\le {} (2r)^p\left( \frac{k+2}{k}\right) ^{p(r-1)}\frac{1}{k^{p(1-r\delta )}} \end{aligned}$$

and we arrive at (2.2).

Example A.3

Let \(R_n=\frac{n^{1-\beta }}{\ln ^\alpha n}\), for some \(\beta \in (0,1]\), \(\alpha \ge 1\) and \(p>1\). Then a weight given by \(U_n=\frac{n^{1-\delta }}{\ln ^\alpha n}\) with \(\delta \in [0,\frac{p-1}{p}\beta )\) is \((p,\{n_k\})\)-admissible w.r.t. \(\{R_n\}\), where \(n_k=[k^r]+1\), \(r=1/\beta\). One can check that (2.1) is easily satisfied. Again using (A.2), we obtain

$$\begin{aligned} \frac{n_{k+1}-n_k}{ U_{n_k}}&\le {} \frac{2r(k+2)^{r-1}\ln ^\alpha n_k}{k^{r(1-\delta )}}\\ &\le {} \frac{2r(k+2)^{r-1}(r+1)^\alpha \ln ^\alpha k}{k^{r(1-\delta )}}\\&= {} 2r(r+1)^\alpha \left( \frac{k+2}{k}\right) ^{r-1}\frac{\ln ^\alpha k}{k^{r(1-\delta )}}. \end{aligned}$$

One can check that the series

$$\begin{aligned} \sum _{k=1}^\infty \frac{\ln ^{\alpha p} k}{k^{pr(1-\delta )}} \end{aligned}$$

converges, if \(pr(1-\delta )>1\). Hence, the condition (2.2) is satisfied.

Example A.4

Now we are going to provide a more general example. Let \(\{G_n\}\) be a weight such that

$$\begin{aligned} \sum _{k=1}^\infty \frac{1}{(G_k)^{p\epsilon }}<\infty \end{aligned}$$
(5.3)

for some \(\epsilon >0\) and \(p>1\). Then a sequence \(\{W_n\}\) is given by

$$\begin{aligned} W_n=(G_n)^{\epsilon +1}, \quad n\in {\mathbb {N}}. \end{aligned}$$

Now, define the sequence \(\{n_k\}\) as follows:

$$\begin{aligned} n_1=1, \quad n_{k+1}=[G_{n_k}]+n_k+1, \quad k\in {\mathbb {N}}. \end{aligned}$$

Then \(\{W_n\}\) is \((p,\{n_k\})\)-admissible w.r.t. \(\{G_n\}\). Indeed,

$$\begin{aligned} \sum _{k=1}^\infty \left( \frac{G_{n_k}}{W_{n_k}}\right) ^p=\sum _{k=1}^\infty \frac{1}{(G_{n_k})^{p\epsilon }}<\infty \end{aligned}$$

which yields (2.1). Let us check the second condition. One has

$$\begin{aligned} \frac{n_{k+1}-n_k}{{{\tilde{W}}}_{n_k}}&= {} \frac{[G_{n_{k}}]+1}{(G_{n_k})^{1+\epsilon }}\\ &\sim {} \frac{1}{(G_{n_k})^{\epsilon }}+ \frac{1}{(G_{n_k})^{\epsilon +1}}\\ &\le {} \frac{1}{(G_{n_k})^{\epsilon }}. \end{aligned}$$

This implies the condition (2.2).

For instance, if we takes \(G_n=n^{1/p}(\ln n)^{\beta +1/p}(\ln \ln n)^\gamma\) (with \(\beta ,\gamma >0\), \(p>1\)), then

$$\begin{aligned} \sum _{k=1}^\infty \frac{1}{(G_n)^{p}}<\infty \end{aligned}$$

hence, \(W_n=G_n^2\) is \((p,\{n_k\})\)-admissible.

Appendix B: More examples with condition (3.8)

Let us consider some examples for which all the above noticed conditions are satisfied.

Example B.1

Let \(\{G_n\}\) and \(\{W_n\}\) be weights considered in Example A.1, i.e. \(G_n=n^{1-\beta }\), \(W_n=n^{1-\delta }\), where \(\beta \in (0,1]\), \(p>1\) and \(\delta \in [0,\frac{p-1}{p}\beta )\). One can see that

$$\begin{aligned} \frac{G_k}{W_k}=\frac{1}{k^{\beta -\delta }} \end{aligned}$$

due to \(\beta -\delta <1\), we infer \(\sum _{k=1}^\infty \frac{G_k}{W_k}=\infty\), while (3.8) is satisfied. Indeed,

$$\begin{aligned} \frac{G_k}{W_k}\left( 1-\frac{W_k}{W_{k+1}}\right)&= {} \frac{1}{k^{\beta -\delta }}\frac{(k+1)^{1-\delta }-k^{1-\delta }}{(k+1)^{1-\delta }}\\ &\le {} \frac{1}{k^{\beta -\delta }}\frac{(1-\delta )k^{-\delta }}{k^{1-\delta }}\\&= {} \frac{1-\delta }{k^{1+\beta -\delta }} \end{aligned}$$

One can see that \(1+\beta -\delta >1\), therefore,

$$\begin{aligned} \sum _{k=1}^\infty \frac{G_k}{W_k}\left( 1-\frac{W_k}{W_{k+1}}\right) <\infty . \end{aligned}$$

Example B.2

Let \(\{R_n\}\) and \(\{U_n\}\) be weights considered in Example A.3, i.e. \(R_n=\frac{n^{1-\beta }}{\ln ^\alpha n}\), \(U_n=\frac{n^{1-\delta }}{\ln ^\alpha n}\), where \(\beta \in (0,1]\), \(\alpha \ge 1\), \(p>1\) and \(\delta \in [0,\frac{p-1}{p}\beta )\). It is clear that

$$\begin{aligned} \sum _{k=1}^\infty \frac{R_k}{U_k}=\infty . \end{aligned}$$

On the other hand, we have

$$\begin{aligned} \frac{R_k}{U_k}\left( 1-\frac{U_k}{U_{k+1}}\right)&= {} \frac{1}{k^{\beta -\delta }}\left( 1-\frac{k^{1-\delta }}{(k+1)^{1-\delta }} \frac{\ln ^\alpha (k+1)}{\ln ^\alpha k}\right) \\ &\le {} \frac{1}{k^{\beta -\delta }}\left( 1-\frac{k^{1-\delta }}{(k+1)^{1-\delta }}\right) \\ &\le {} \frac{1-\delta }{k^{1+\beta -\delta }} \end{aligned}$$

Hence, the series

$$\begin{aligned} \sum _{k=1}^\infty \frac{R_k}{U_k}\left( 1-\frac{U_k}{U_{k+1}}\right) \end{aligned}$$

converges.

Example B.3

Let us provide an other example of p-admissible weight. We are going to establish that the weight considered in Example 2.1 is indeed p-admissible.

Let \(G_n=(\ln n)^{\beta +1/p}(\ln \ln n)^\gamma\) with \(\beta >0\), \(\gamma \ge 1\), and \(n_m=[m^r]+1\), \(r=1/\alpha\) with \(\alpha \in (0,1]\). Define

$$\begin{aligned} W_n=n^{\delta /p}(\ln n)^{\beta +1/p}(\ln \ln n)^\gamma , \quad \delta \ge p(1-\alpha )+1. \end{aligned}$$

Then \(\{W_n\}\) is p-admissible w.r.t. \(\{G_n\}\). Indeed, we first note that

$$\begin{aligned} \sum _{m=1}^\infty \frac{1}{n_m}<\infty \end{aligned}$$

therefore

$$\begin{aligned} \sum _{k=1}^\infty \left( \frac{G_{n_m}}{W_{n_m}}\right) ^p=\sum _{m=1}^\infty \frac{1}{n_m^{\delta }}<\infty . \end{aligned}$$

Furthermore, using the same argument of Example A.1

$$\begin{aligned} \frac{n_{m+1}-n_m}{W_{n_m}}&= \frac{n_{m+1}-n_m}{n_m^{\delta /p}G_{n_m}}\\ &\le {} \frac{(m+1)^r+1-m^r}{m^{(1-\tau )r}G_{n_m}} \\&= {} 2r\left( \frac{m+2}{m}\right) ^{r-1}\frac{1}{m^{1-r\tau }G_{n_m}}, \end{aligned}$$

where \(\tau =(p-\delta )/p\). Hence,

$$\begin{aligned} \left( \frac{n_{m+1}-n_m}{W_{n_m}}\right) ^p &\sim {} \frac{1}{m^{(1-r\tau )p}G^p_{n_m}}\\ &\sim {} \frac{1}{m^{(1-r\tau )p}(\ln m)^{\beta p+1}(\ln \ln m)^{\gamma p}}. \end{aligned}$$

Consequently, if \((1-r\tau )p\ge 1\), i.e. \(\delta \ge p(1-\alpha )+1\), the series

$$\begin{aligned} \sum _{m=1}^\infty \frac{1}{m^{(1-r\tau )p}(\ln n_m)^{\beta p+1}(\ln \ln n_m)^{\gamma p}} \end{aligned}$$

converges. So, \(\{W_n\}\) is p-admissible w.r.t. \(\{G_n\}\).

Let us establish that the weights \(\{G_n\}\) and \(\{W_n\}\) satisfy the condition (3.8). For the sake of simplicity, we assume that \(\delta =1\). Then

$$\begin{aligned} \frac{G_k}{W_k}\left( 1-\frac{W_k}{W_{k+1}}\right)&= {} \frac{(k+1)^{1/p}G_{k+1}-k^{1/p}G_{k}}{k^{1/p}(k+1)^{1/p}G_{k+1}} \end{aligned}$$
(B.1)

Now considering the derivative of \(\psi (x)=x^{1/p}(\ln x)^{\beta +1/p}(\ln \ln x)^\gamma\), we can estimate RHS of (B.1) as follows

$$\begin{aligned} \frac{(k+1)^{1/p}G_{k+1}-k^{1/p}G_{k}}{k^{1/p}(k+1)^{1/p}G_{k+1}}\le \frac{C}{k^{1+1/p}}, \quad k\in {\mathbb {N}} \end{aligned}$$

for some constant. This implies the convergence of the series

$$\begin{aligned} \sum _{k=1}^\infty \frac{G_k}{W_k}\left( 1-\frac{W_k}{W_{k+1}}\right) . \end{aligned}$$

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mukhamedov, F. Weighted laws of large numbers and convergence of weighted ergodic averages on vector valued \(L_p\)-spaces. Adv. Oper. Theory 6, 57 (2021). https://doi.org/10.1007/s43036-021-00153-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s43036-021-00153-2

Keywords

Mathematics Subject Classification

Navigation