R.DPOIS Function (Gnumeric)

• Introduced: First release not established; named in Gnumeric 1.12.10 release notes.
• Supported in: Gnumeric 1.12.62; no retirement is established.
• Scope: Desktop Gnumeric with its Statistical Functions From R plugin. English comma-separated formulas are shown.
• Checked: October 14, 2026. Tables and the named advanced check use 1.12.57 ssconvert. Current 1.12.62 source was inspected; that release was not executed.

R.DPOIS returns the Poisson probability mass P(X=k), using the expected count for the observation interval as its mean. It does not return an accumulated probability or a rate per unit time. Versioned function help.

=R.DPOIS(events,mean[,give_log])

• events: integer count for the point probability.
• mean: nonnegative expected count for the same exposure interval.
• give_log: optional FALSE; TRUE returns the natural logarithm of the density or probability mass.

Brackets mark optional arguments; do not type them. Current worksheet implementation.

These self-contained formulas were recalculated natively. Ordinary-domain results were checked against independent mathematics; source guards explain the boundary cases. Results are rounded to twelve decimal places, or thirteen significant digits for small nonzero values. This is presentation precision, not a universal accuracy guarantee.

With mean 2, exactly two events has probability 0.270670566473, from EXP(-2)*2^2/FACT(2). Zero events has probability 0.135335283237. For mean 4, exactly four events gives 0.195366814813.

If a stated model has three events per hour but the observation interval is twenty minutes, the expected count is 1. The independent zero-event probability is then EXP(-1), approximately 0.367879441171. Keep the rate and exposure units consistent; the function does not perform that conversion automatically.

For positive mean λ, neighboring masses satisfy P(X=k+1)/P(X=k)=λ/(k+1). The saved check at k=2 and λ=2 gives 2/3. This is a useful recurrence check independent of a factorial implementation.

For independent observations 1, 2 and 3 under a common mean of 2, the sum of the three log masses is approximately −4.326023566428, independently calculated. Adding direct log results avoids first multiplying small masses. Independence and a suitable count model are assumptions of that likelihood example.

The saved advanced-check result for =R.DPOIS(3,2)/R.DPOIS(2,2) was 0.666666666667.

Mean zero represents a point mass at zero: k=0 returns 1 and positive k returns zero. Negative mean gives #NUM!. A genuinely fractional count such as 2.9 returns zero mass rather than being floored. The helper tolerates tiny near-integer differences, so 2.000000000000001 matches the count 2 in the tested build.

Negative counts have zero mass. A requested log of zero becomes #NUM!, while log mass at mean zero and count zero is 0. Empty F5 acts as zero; numeric text is converted; nonnumeric text gives #VALUE!; wrong arity gives #N/A.

F5 is genuinely empty, rather than a cell containing an empty string.

• Current worksheet callback
• Tested-version worksheet callback
• Current dpois calculation
• Tested-version dpois calculation
• Nonfinite worksheet-value handling
• Statistical Functions From R plugin declaration
• Near-integer tolerance
• Noninteger mass check

The deliberate fractional count/trial probes also emitted noninteger-input calculation warnings. The saved logs retain them.

The relevant complete worksheet callback and main calculation helper are unchanged between the inspected versions. That does not establish later-version numerical execution. Both stale and uncached SUM controls recalculated correctly. Native XML preserves the R.* identities. The secondary ODF export keeps these calls in the ORG.GNUMERIC namespace; it does not establish execution in another product. GUI entry, other locales and other spreadsheet products were not tested.

POISSON, R.DGAMMA, FACT.