17 citations as recorded by crossref.

1. MULTIFRACTAL SURFACES: LUCENA AND STANLEY APPROACHES G. CORSO & D. MOREIRA https://doi.org/10.1142/S0218348X13500205
2. Anomalies and cycles of precipitable water over Iran in recent decades H. Asakereh et al. https://doi.org/10.1007/s12517-015-1888-2
3. Anthropogenic CO 2 warming challenged by 60-year cycle F. Gervais https://doi.org/10.1016/j.earscirev.2016.02.005
4. Modified wavelet variation for the Hermite processes L. Loosveldt & C. Tudor https://doi.org/10.1214/25-EJS2390
5. On the variability of ENSO at millennial timescales G. Wang & A. Tsonis https://doi.org/10.1029/2008GL035092
6. FARIMA processes with application to biophysical data K. Burnecki https://doi.org/10.1088/1742-5468/2012/05/P05015
7. Cracking the Climate Change Conundrum with Derivatives D. Bloch et al. https://doi.org/10.1002/wilj.41
8. Testing of fractional Brownian motion in a noisy environment M. Balcerek & K. Burnecki https://doi.org/10.1016/j.chaos.2020.110097
9. A new method of detecting abrupt dynamic change based on rescaled range analysis . Deng Bei-Sheng et al. https://doi.org/10.7498/aps.59.8264
10. Discrete-time autoregressive model for unequally spaced time-series observations F. Elorrieta et al. https://doi.org/10.1051/0004-6361/201935560
11. Stochastic simulations of the Madden–Julian oscillation activity C. Jones & L. Carvalho https://doi.org/10.1007/s00382-009-0660-2
12. Estimation of FARIMA Parameters in the Case of Negative Memory and Stable Noise K. Burnecki & G. Sikora https://doi.org/10.1109/TSP.2013.2253773
13. Heterogeneity of Scaling of the Observed Global Temperature Data S. Blesić et al. https://doi.org/10.1175/JCLI-D-17-0823.1
14. A new method for abrupt dynamic change detection of correlated time series W. He et al. https://doi.org/10.1002/joc.2367
15. Tiny warming of residual anthropogenicCO2 F. Gervais https://doi.org/10.1142/S0217979214500957
16. Properties and changes in empirical orthogonal components of temperature fields in Northern Eurasia in the 20th century N. Datsenko et al. https://doi.org/10.1134/S0001433811010051
17. Combined Methodology for Linear Time Series Forecasting R. Moraes Muniz da Silva et al. https://doi.org/10.1002/tee.23252