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haze vs tbrf

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

Shared themes:r-package

haze vs tbrf: at a glance

Featurehazetbrf
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesneuroimaging, mesh-processing, interpolation, r-packagerolling-statistics, water-quality, time-series, environmental-data
Last editorial update6h ago45m ago
WebsiteVisit →Visit →

What is haze?

Four dormant years end with a modernization pass and an off-by-one fix in the C++ core

haze does nearest-neighbour smoothing and k-d tree interpolation on brain surface meshes. It sat untouched from April 2022 until July 2026, when a single release modernized it for current R versions and corrected an off-by-one error in the C++ code. It is not on CRAN and never will be — the package exceeds 50MB against CRAN's 5MB ceiling, a constraint its own initial release notes acknowledge.

Read the full haze trajectory →

What is tbrf?

Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.

tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.

Read the full tbrf trajectory →

haze vs tbrf: editorial side-by-side

H
haze
ANALYTICS
2.5

Four dormant years end with a modernization pass and an off-by-one fix in the C++ core

◆ Current state

haze does nearest-neighbour smoothing and k-d tree interpolation on brain surface meshes. It sat untouched from April 2022 until July 2026, when a single release modernized it for current R versions and corrected an off-by-one error in the C++ code. It is not on CRAN and never will be — the package exceeds 50MB against CRAN's 5MB ceiling, a constraint its own initial release notes acknowledge.

◆ Where it's heading

The July 2026 release arrived 56 minutes after its sibling regfusionr 0.3.0 from the same maintainer, which is the tell: this is a maintainer sweeping a set of related neuroimaging packages back into working order, not independent development on haze itself. haze is the dependency, regfusionr the consumer, and the substantive work sits on the regfusionr side. The off-by-one correction is the only change here that alters results.

◆ Prediction

Expect haze to move only when a downstream dfsp-spirit package needs it to — its cadence is driven by the sibling packages, not by its own roadmap.

T
tbrf
ANALYTICS
0.0

Time-based rolling statistics for water-quality data, finally getting plotting and padding built in.

◆ Current state

tbrf computes rolling statistics over time windows rather than fixed row counts — geometric means, confidence intervals and related summaries indexed by date. That distinction matters for irregularly sampled environmental monitoring data, where a fixed-width window spans different amounts of real time. Version 0.1.7 folds in stat_stepribbon() from ggalt, ships an Entero example dataset for lognormal workflows, and adds na.pad across the tbr_ family.

◆ Where it's heading

The package spent its middle releases absorbing upstream breakage — a lubridate duration redefinition, a tibble 3.0.0 subassignment change, tidyselect internals. The 0.1.7 release breaks that pattern: it is the first in five years to add capability rather than repair it, and it does so by internalising a stat from an abandoned dependency instead of relying on it. Cadence remains very low, with a five-year gap between 0.1.5 and 0.1.6.

◆ Prediction

Absorbing stat_stepribbon() directly suggests further vendoring of the plotting layer rather than new statistical functions. The entries do not indicate which rolling statistics, if any, are queued next.

Alternatives to haze and tbrf

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 haze or tbrf.

See all haze alternatives → · See all tbrf alternatives →

Recent activity from haze and tbrf

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

  1. 18d agohazeVersion 0.3.0 -- Fixes and modernization
  2. 0y agotbrfstat_stepribbon vendored in, plus na.pad on all rolling functions
  3. 1y agotbrfgm_mean_ci forwards na.rm and zero.propagate correctly
  4. 4y agohazev0.2.0 -- kdtrees
  5. 4y agohazev0.1.0: Initial release
  6. 6y agotbrfFix internals broken by tibble 3.0.0 subassignment
  7. 6y agotbrfDate windows recomputed with intervals and periods

Frequently asked questions

What is the difference between haze and tbrf?

Both compete on the same themes — r-package — within Analytics. haze is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is haze better than tbrf?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. haze is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to haze?

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

What are the best alternatives to tbrf?

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