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pql

A Partitioned Quasi-Likelihood for Distributed Statistical Inference

In the big data setting, working data sets are often distributed on multiple machines. However, classical statistical methods are often developed to solve the problems of single estimation or inference. We employ a novel parallel quasi-likelihood method in generalized linear models, to make the variances between different sub-estimators relatively similar. Estimates are obtained from projection subsets of data and later combined by suitably-chosen unknown weights. The philosophy of the package is described in Guo G. (2020) <doi:10.1007/s00180-020-00974-4>.

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VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 pql_0.1.0.tar.gz 29.7 KiB
0.1.0 rolling linux/noble R-4.5 pql_0.1.0.tar.gz 29.6 KiB
0.1.0 rolling source/ R- pql_0.1.0.tar.gz 3.7 KiB
0.1.0 latest linux/jammy R-4.5 pql_0.1.0.tar.gz 29.7 KiB
0.1.0 latest linux/noble R-4.5 pql_0.1.0.tar.gz 29.6 KiB
0.1.0 latest source/ R- pql_0.1.0.tar.gz 3.7 KiB
0.1.0 2026-04-26 source/ R- pql_0.1.0.tar.gz 3.7 KiB
0.1.0 2026-04-23 source/ R- pql_0.1.0.tar.gz 3.7 KiB
0.1.0 2026-04-09 windows/windows R-4.5 pql_0.1.0.zip 32.2 KiB
0.1.0 2025-04-20 source/ R- pql_0.1.0.tar.gz 3.7 KiB

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