TY  - JOUR
T1  - Utilizing symmetric Phi-divergence in serial independence testing
AU  - Ashtari Nezhad, Emad
PY  - 2025
DA  - June
Y2  - 2025
DO  - 10.15672/hujms.1586978
JF  - Hacettepe Journal of Mathematics and Statistics
PB  - Hacettepe University
WT  - DergiPark
SN  - 2651-477X
SP  - 1206
EP  - 1235
VL  - 54
IS  - 3
LA  - en
AB  - This manuscript introduces a novel class of time series independence tests based on Phi-divergence and quantile-based symbolization. We derive the asymptotic distribution of the test statistic and propose a bootstrap version. Simulations identified optimal parameter values and compared the test performance to existing methods, demonstrating higher size-corrected power for specific Phi-divergence cases. Furthermore, we investigate Rukhin and power divergence, revealing Pearson’s divergence as optimal. The proposed tests were applied to financial (Tehran Stock Exchange, S\&P 500) and ecological (Lynx population) datasets, effectively detecting dependence on the data and confirming the adequacy of the model through independent residuals, demonstrating the robustness and versatility of the method in diverse domains.
KW  - Serial independence test
KW  - Phi-divergence
KW  - simulation studies
KW  - quantile
symbolization
KW  - time series
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UR  - https://doi.org/10.15672/hujms.1586978
L1  - https://dergipark.org.tr/en/download/article-file/4373950
ER  -