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* On my machine, the Fenwick approach outperforms the naive approach around $n=$ `r intersection_n_time_rounded[1]` and the naive C++ approach around $n=$ `r intersection_n_time_rounded[2]`. Theoretically, the naive approach is $\mathcal{O}(n^2)$ in time, while the Fenwick approaches is $\mathcal{O}(n \log n)$.
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* The naive approach always uses more memory than the fenwick approach, which uses more memory than the C++ approach. Theoretically, the naive approach is $\mathcal{O}(n^2)$ in memory, while the Fenwick and C++ approaches are $\mathcal{O}(n)$.
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* On my machine, the Fenwick C++ approach outperforms the naive R approach around $n=$ `r intersection_n_time_rounded[1]` and the naive C++ approach around $n=$ `r intersection_n_time_rounded[2]`. Theoretically, the naive approaches are $\mathcal{O}(n^2)$ in time, while the Fenwick approach is $\mathcal{O}(n \log n)$.
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* The naive R approach always uses more memory than the Fenwick and naive C++ approaches. Theoretically, the naive R approach is $\mathcal{O}(n^2)$ in memory, while the Fenwick and naive C++ approaches are $\mathcal{O}(n)$.
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* All C++ implementations use `cpp11` (no Rcpp dependency) for faster compilation.
"Description": "A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.",
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