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Comparison · Analytics
distributions3 vs omock
A side-by-side editorial comparison of distributions3 and omock — release velocity, themes, recent moves, and the top alternatives to consider.
distributions3 vs omock: at a glance
What is distributions3?
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.
What is omock?
A mock-data generator for OMOP studies that keeps widening what it can fake.
omock builds synthetic OMOP Common Data Model tables so packages in the darwin-eu and OHDSI ecosystem can be tested without touching patient data. The 0.7.0 release adds concept set subsetting with its own vignette, unit and value support in mockMeasurement, observation date validation and cohort attrition initialization, while deprecating mockConcepts. Releases arrive as PR digests rather than written notes.
distributions3 vs omock: editorial side-by-side
distributions3
6.3ANALYTICS
distributions3 0.3.0 adds sample-based distributions and likelihood derivatives
◆ Current state
An R package giving probability distributions a consistent object interface - d/p/q/r functions, moments, and prodist() methods that pull a fitted distribution out of a regression object. Version 0.3.0 is the first substantive release under Achim Zeileis's maintenance, and it widens what a distribution is allowed to be: Empirical() represents a distribution by a random sample rather than by parameters, and numerical fallbacks now fill in cdf(), pdf(), quantile(), random() and the moments for any object that implements only some of them. New score() and hessian() generics compute first and second derivatives of the log-likelihood with respect to the parameters, analytically for a few distributions and numerically for the rest.
◆ Where it's heading
Growth used to arrive as new distribution families contributed from outside - the extreme-value set, Erlang, later the Poisson binomial. This release changes the axis: alongside two new distributions it adds an inference layer (score, hessian) and a forecast-evaluation one (crps() methods against scoringRules), which are capabilities about distributions rather than more of them. Dependency weight is being cut at the same time, with ggplot2 demoted to Suggests and glue replaced by base R sprintf().
◆ Prediction
With numeric fallbacks and the derivative generics in place, expect analytic score() and hessian() methods to be filled in across more of the distribution catalogue. The constructor-default change is the likeliest source of follow-up fixes, since calls like Poisson() now return a length-zero distribution where they previously errored.
omock
0.0ANALYTICS
A mock-data generator for OMOP studies that keeps widening what it can fake.
◆ Current state
omock builds synthetic OMOP Common Data Model tables so packages in the darwin-eu and OHDSI ecosystem can be tested without touching patient data. The 0.7.0 release adds concept set subsetting with its own vignette, unit and value support in mockMeasurement, observation date validation and cohort attrition initialization, while deprecating mockConcepts. Releases arrive as PR digests rather than written notes.
◆ Where it's heading
The package has been moving from generating tables to shipping and managing reference datasets — mockDatasets arrived in 0.4.0, mockCdmFromDataset gained a source argument in 0.5.0, and 0.6.1 added download retry handling plus an internal GiBleed dataset after the hosted files moved. The recent work is filling in CDM fidelity: type concepts, measurement units, attrition, and guards for degenerate cases like an empty person table.
◆ Prediction
Expect coverage to keep extending table by table toward the parts of the CDM that omock still cannot mock, with mockConcepts removed outright once the concept set subsetting path settles.
Alternatives to distributions3 and omock
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 distributions3 or omock.
Lightdash
Lightdash keeps handing authoring to outside agents and keeping the governed layer for itself.
Delta Lake
A 4.4.0 tag appears, but the feed carries only its release plumbing
Basedash
Basedash keeps pushing its data out of the workspace — now to people without accounts
RStudio
RStudio ships through release branches, and the notes are commit messages
dbt Core
dbt Fusion's second beta is adapter work: ClickHouse gets materializations, indexes, and catalogs
See all distributions3 alternatives → · See all omock alternatives →
Recent activity from distributions3 and omock
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11h agodistributions3Empirical distributions, plus score and hessian generics ⚡
- 29d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
- 2mo agoomockConcept set subsetting and richer measurement mocks
- 4mo agoomockDelphi dataset added and CDM version bumped
- 6mo agoomockDataset downloads survive the storage move
- 10mo agodistributions3ggplot2 compatibility for the plotting functions
- 11mo agoomockJOSS submission tag alongside the 0.5.0 release
- 11mo agoomockmockCdmFromDataset gains a source argument
- 1y agoomockmockDatasets introduces bundled reference data
- 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
- 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
- 4y agodistributions3Extreme-value family, Erlang, and a plotting generic
Frequently asked questions
What is the difference between distributions3 and omock?
They serve adjacent needs but don't currently overlap on shipped themes. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 distributions3 better than omock?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 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 distributions3?
Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.
What are the best alternatives to omock?
Top omock alternatives in Analytics are ranked by recent ship velocity. Browse the "omock alternatives" section above for the current picks, or visit /alternatives/omock-r for the full list with editorial commentary on each.