LINEST Function (OpenOffice Calc)

• Introduced: First release not established; documented by OpenOffice.org 3.3.
• Supported in: Apache OpenOffice 4.1.16; this is a verified release, not a final supported version.
• Scope: Desktop Calc, English function names and semicolon-separated formulas.
• Checked: October 14, 2026. Eight ordinary scalar or INDEX-selected reference formulas were recalculated from generated ODF in 4.1.16 on Linux x86-64, Build 9816. Source and independent arithmetic were checked.

LINEST returns least-squares linear coefficients and, optionally, a matrix of fit statistics. For one predictor with an intercept, the first result row is slope then intercept. It does not return predicted y values; TREND or a coefficient formula does that. Release implementation.

LINEST(KnownY[;KnownX[;Constant[;Statistics]]])

• KnownY: required observed responses. KnownX: optional predictors, defaulting to a simple 1,2,… sequence when omitted.
• Constant: optional TRUE by default; FALSE forces a zero intercept.
• Statistics: optional FALSE by default; TRUE requests five result rows. The examples explicitly enable both flags.

Enter the following numbers in their stated worksheet rows. K14 is unused; the prediction range is K10:K13.

GROWTH uses the positive values in L10:L14. The other regression examples use J10:J14. Keep each observed x-y pair aligned.

The native column contains saved 4.1.16 results; independent references use high-precision arithmetic and the stated source rules. Values are shown to twelve decimal places where needed. The range examples use the numeric setup above.

For the given five x-y pairs, the coefficient row is 3.2,1.8, defining y=1.8+3.2x. With Statistics=TRUE, row 3 contains R² and residual standard error, row 4 contains F and residual degrees of freedom, and row 5 contains regression and residual sums of squares.

The native component examples give R²≈0.992248062016, residual standard error≈0.516397779494, F=384 and degrees of freedom=3. The sums of squares are 102.4 explained and 0.8 residual.

Five observations minus two fitted coefficients leaves three residual degrees of freedom. The residual standard error is sqrt(0.8/3), and R²=102.4/(102.4+0.8)=128/129. For this one-predictor fit, F=102.4/(0.8/3)=384. These identities independently reconcile the output positions.

Row 2, documented by the source, contains coefficient standard errors; the native table here selects other components. Statistical inference from standard errors or F requires assumptions about the model and residuals. A high R² alone does not establish causation, adequate residual behavior or out-of-sample accuracy.

The matrix checker requires numeric entries, compatible shapes and enough samples. Multiple-predictor output ordering and rank deficiency require additional care; the native examples are explicitly a one-predictor, full-rank fit with nonzero residuals. Invalid shapes, text entries and exact-fit special cases were not executed.

INDEX selects the one-based row and column stated in each formula. The evidence establishes those scalar components, not full GUI array entry or automatic placement of the five-row result. Preserve the distinction between coefficients, predicted values and fit statistics.

TREND, SLOPE, INTERCEPT.

• Function-specific release implementation
• CheckMatrix regression helper
• CalulateRGPRKP regression helper

The generated ODF produced the informational load warning “Not all attributes could be read.” The sheet was hard-recalculated and saved separately. All eight ordinary formula identities, inputs and selected results were reconciled; a stale SUM cache changed from 999999 to 3 and an uncached SUM returned 7. This establishes the stated examples, not every workbook style, invalid input or GUI whole-array entry. INDEX wrappers select individual returned components. Other explanatory identities are independent calculations. The authoring-tool XLSX was not executed in OpenOffice, and its preview values are not the native results reported here.