Bai, Z. D.; Cheng, Philip E. Marcinkiewicz strong laws for linear statistics. (English) Zbl 0960.60026 Stat. Probab. Lett. 46, No. 2, 105-112 (2000). Summary: Strong laws are established for linear statistics that are weighted sums of a random sample. We show extensions of the Marcinkiewicz-Zygmund strong law under certain moment conditions on both the weights and the distribution. These complement the results of J. Cuzick [J. Theor. Probab. 8, No. 3, 625-641 (1995; Zbl 0833.60031)] and the authors and C. H. Zhang [Stat. Sin. 7, 923-928 (1997)]. Cited in 14 ReviewsCited in 43 Documents MSC: 60F15 Strong limit theorems 62G05 Nonparametric estimation Keywords:Hardy-Littlewood strong law; Marcinkiewicz-Zygmund strong law; weighted sums of i.i.d. random variables PDF BibTeX XML Cite \textit{Z. D. Bai} and \textit{P. E. Cheng}, Stat. Probab. Lett. 46, No. 2, 105--112 (2000; Zbl 0960.60026) Full Text: DOI References: [1] Bai, Z.D., Cheng, P.E., Zhang, C.H., 1997. An extension of the Hardy-Littlewood strong law. Statist. Sinica, 923-928. · Zbl 1067.60501 [2] Cheng, P.E., A note on strong convergence rates in nonparametric regression, Statist. probab. lett., 24, 357-364, (1995) · Zbl 0835.62046 [3] Cuzick, J., A strong law for weighted sums of i.i.d. random variables, J. theoret. probab, 8, 625-641, (1995) · Zbl 0833.60031 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.