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mutagen vs spmodel

A side-by-side editorial comparison of mutagen and spmodel — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

mutagen vs spmodel: at a glance

Featuremutagenspmodel
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-manipulation, tidyverse, stata-port, r-packagespatial-statistics, regression-modelling, kriging, r-package
Last editorial update1h ago8h ago
WebsiteVisit →Visit →

What is mutagen?

A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release

mutagen provides row-wise column-generation helpers for R data frames in the spirit of Stata's egen — gen_rowmean(), gen_rowsum(), gen_rowsd(), gen_rownonmiss() and about a dozen siblings. It reached 0.5.0 within three months of its first release, adding two or three functions each time. The most recent release adds gen_coldiff() and renames two functions to fit the naming scheme.

Read the full mutagen trajectory →

What is spmodel?

Spatial regression in R, adding block kriging and then tuning the numerics underneath it

spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.

Read the full spmodel trajectory →

mutagen vs spmodel: editorial side-by-side

M
mutagen
ANALYTICS
0.0

A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release

◆ Current state

mutagen provides row-wise column-generation helpers for R data frames in the spirit of Stata's egen — gen_rowmean(), gen_rowsum(), gen_rowsd(), gen_rownonmiss() and about a dozen siblings. It reached 0.5.0 within three months of its first release, adding two or three functions each time. The most recent release adds gen_coldiff() and renames two functions to fit the naming scheme.

◆ Where it's heading

The package is filling out a known surface rather than discovering one: the reference implementation exists in Stata, so development is a matter of working through the list. Alongside that, the naming convention is still settling — gen_rowmatch became gen_rowany, gen_percent became gen_colpercent, gen_na_listcol became gen_listcol_na — which is normal for a pre-1.0 package but means callers should expect further renames. Contributions are arriving from several first-time contributors.

◆ Prediction

The gen_col* prefix has only two members against a dozen gen_row* functions, so column-wise coverage is the obvious gap; expect it to fill before the naming stabilises for a 1.0.

S
spmodel
ANALYTICS
0.0

Spatial regression in R, adding block kriging and then tuning the numerics underneath it

◆ Current state

spmodel fits spatial linear and generalised linear models, for both point-referenced and areal data, with prediction and diagnostics attached. Block prediction arrived in 0.11.0 and the releases since have refined it. The most recent release changes optimiser behaviour: the default Nelder-Mead relative stopping tolerance tightens from 1e-4 to 1e-6 to reduce convergence on local rather than global maxima.

◆ Where it's heading

Two threads run in parallel. The first is expanding what can be predicted — point predictions, then areal averages over a region via block kriging, then better accuracy and efficiency for that path as the block size default moved from 1000 to 4000 in 0.12.0. The second is numerical trustworthiness, and it is unusually prominent here: a range-constraint option for stability in 0.9.0, a corrected log determinant of the fixed effects in the restricted log likelihood in 0.11.0, a cloud semivariogram that had been doubling the semivariance fixed in 0.11.1, and now a tighter optimiser tolerance. Several of these silently changed results before they were caught.

◆ Prediction

Expect the maintainers to keep publishing explicit reproduction instructions alongside numerical default changes, as 0.13.0 does by documenting the `control = list(reltol = 1e-4)` escape hatch. The entries give no signal of expansion beyond the current model families.

Alternatives to mutagen and spmodel

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either mutagen or spmodel.

See all mutagen alternatives → · See all spmodel alternatives →

Recent activity from mutagen and spmodel

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 2mo agospmodelTighter optimiser tolerance to avoid local maxima
  2. 6mo agospmodelEmpirical autocovariance function and better block kriging accuracy
  3. 8mo agomutagengen_coldiff() added; two functions renamed for consistency
  4. 9mo agospmodelCloud semivariogram doubling fixed; geometry warnings added
  5. 9mo agomutagengen_rowsum() and gen_rowsd() added
  6. 9mo agomutagengen_rownonmiss() and gen_rowall() added
  7. 9mo agomutagenRow mean, median and missingness helpers; gen_rowmatch renamed
  8. 11mo agomutagenFirst release with the row-wise gen_* family
  9. 1y agospmodelBlock kriging for areal averages and their uncertainty
  10. 1y agospmodelRobust semivariogram and new covariance types for areal models
  11. 1y agospmodelRange constraint option and redefined covariance type names

Frequently asked questions

What is the difference between mutagen and spmodel?

Both compete on the same themes — r-package — within Analytics. mutagen and spmodel are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is mutagen better than spmodel?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mutagen and spmodel are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to mutagen?

Top mutagen alternatives in Analytics are ranked by recent ship velocity. Browse the "mutagen alternatives" section above for the current picks, or visit /alternatives/mutagen-r for the full list with editorial commentary on each.

What are the best alternatives to spmodel?

Top spmodel alternatives in Analytics are ranked by recent ship velocity. Browse the "spmodel alternatives" section above for the current picks, or visit /alternatives/spmodel for the full list with editorial commentary on each.