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Minor updates on README
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README.Rmd

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@@ -38,12 +38,12 @@ The package **splines2** provides functions to construct basis matrices of
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In addition to the R interface, **splines2** provides a C++ header-only library
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integrated with **Rcpp**, which allows the construction of spline basis
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functions directly in C++ with the help of **Rcpp** and **RcppArmadillo**.
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Thus, it can also be treated as one of the **Rcpp\*** packages. A toy example
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package that uses the C++ interface is available [here][example-pkg].
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Thus, it can also be treated as one of the **Rcpp\*** packages.
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A toy example package that uses the C++ interface is available
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[here][example-pkg].
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## Installation of CRAN Version
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You can install the released version from [CRAN][cran-url].
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```R
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## Performance
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Since v0.3.0, the implementation of the main functions has been rewritten in C++
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with the help of the **Rcpp** and **RcppArmadillo** packages. The computational
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performance has thus been boosted and comparable with the function
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`splines::splineDesign()`.
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Since version 0.3.0, the implementation of the main functions has been rewritten
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in C++ with the help of the **Rcpp** and **RcppArmadillo** packages.
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The computational performance has thus been boosted and comparable with the
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function `splines::splineDesign()`.
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Some quick micro-benchmarks are provided below for reference.
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```
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The **splines** package does not contain an implementation for integrals of
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B-splines. Thus, we performed a comparison with package **ibs** (version `r
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packageVersion("ibs")`), where the function `ibs::ibs()` was also implemented in
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**Rcpp**.
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B-splines. Thus, we performed a comparison with package **ibs** (version
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`r packageVersion("ibs")`), where the function `ibs::ibs()`
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was also implemented in **Rcpp**.
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```{r bench-ibs}
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## integrals of B-splines

README.md

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@@ -70,7 +70,7 @@ for all functions and contains the following vignettes:
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## Performance
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Since v0.3.0, the implementation of the main functions has been
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Since version 0.3.0, the implementation of the main functions has been
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rewritten in C++ with the help of the **Rcpp** and **RcppArmadillo**
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packages. The computational performance has thus been boosted and
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comparable with the function `splines::splineDesign()`.
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Unit: relative
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expr min lq mean median uq max neval
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splines::bs 3.7654 3.4269 2.9937 3.2721 2.6982 2.2310 100
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splines::splineDesign 2.2060 1.9829 2.0429 2.1138 1.8133 9.7254 100
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splines::bs 3.7488 3.4227 2.9600 3.2924 2.6877 1.9122 100
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splines::splineDesign 2.2028 1.9788 2.0333 2.1305 1.8288 8.2016 100
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splines2::bSpline 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 100
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Similarly, for derivatives of B-splines, `splines2::dbs()` provides
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```
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Unit: relative
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expr min lq mean median uq max neval
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splines::splineDesign 2.6044 2.4404 2.1964 2.2872 2.2623 1.7084 100
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splines2::dbs 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 100
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expr min lq mean median uq max neval
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splines::splineDesign 2.6498 2.4535 2.193 2.2861 2.1459 1.558 100
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splines2::dbs 1.0000 1.0000 1.000 1.0000 1.0000 1.000 100
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The **splines** package does not contain an implementation for integrals
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of B-splines. Thus, we performed a comparison with package **ibs**
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(version `r packageVersion("ibs")`), where the function `ibs::ibs()` was
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also implemented in **Rcpp**.
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(version 1.4), where the function `ibs::ibs()` was also implemented in
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**Rcpp**.
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``` r
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## integrals of B-splines
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Unit: relative
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expr min lq mean median uq max neval
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ibs::ibs 23.677 21.335 19.921 21.505 20.879 5.2521 100
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splines2::ibs 1.000 1.000 1.000 1.000 1.000 1.0000 100
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ibs::ibs 24.306 21.108 22.016 21.621 21.342 26.533 100
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splines2::ibs 1.000 1.000 1.000 1.000 1.000 1.000 100
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The function `ibs::ibs()` returns the integrated B-splines instead of
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the integrals of spline basis functions. Thus, we applied the same
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```
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Unit: relative
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expr min lq mean median uq max neval
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splines::ns 4.9949 4.7999 4.6694 4.4282 5.014 4.924 100
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splines2::nsp 1.0000 1.0000 1.0000 1.0000 1.000 1.000 100
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expr min lq mean median uq max neval
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splines::ns 4.9751 4.7263 4.6571 4.4456 4.8987 5.274 100
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splines2::nsp 1.0000 1.0000 1.0000 1.0000 1.0000 1.000 100
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The functions `bSpline()` and `mSpline()` produce periodic spline basis
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functions based on B-splines and M-splines, respectively, when
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Unit: relative
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expr min lq mean median uq max neval
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pbs::pbs 4.1061 3.9837 3.37071 3.8543 3.6758 1.26136 100
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pbs::pbs 4.0864 3.9469 3.34075 3.8658 3.6311 1.23830 100
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splines2::bSpline 1.0000 1.0000 1.00000 1.0000 1.0000 1.00000 100
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splines2::mSpline 1.1667 1.1493 0.97082 1.1416 1.1429 0.15675 100
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splines2::mSpline 1.1598 1.1350 0.95918 1.1516 1.1169 0.12212 100
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<details>
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<summary>

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