GROWTH Function (LibreOffice Calc)
The GROWTH function in LibreOffice Calc returns predicted Y-values based on exponential regression. This guide explains syntax, forecasting behavior, examples, errors, and best practices.
Compatibility
▾| Excel | ✔ |
| Gnumeric | ✔ |
| Google_sheets | ✔ |
| Libreoffice | ✔ |
| Numbers | ✖ |
| Onlyoffice | ✔ |
| Openoffice | ✔ |
| Wps | ✔ |
| Zoho | ✔ |
What the GROWTH Function Does â–¾
- Predicts Y-values based on an exponential regression model
- Works with one or more independent variables
- Supports forecasting future values
- Works as an array function (spills in modern Calc)
- Can fill missing values or extend exponential trends
- Works across sheets
GROWTH is the easiest way to generate exponential forecasts.
Syntax â–¾
GROWTH(known_y; known_x; new_x; const)
Where:
known_y— dependent variable (must be positive)known_x— independent variable(s)new_x— X values to predict forconst— TRUE = calculate intercept; FALSE = force intercept = 1
If
new_x is omitted, GROWTH predicts Y-values for the same X-values in known_x.
Basic Examples â–¾
Predict Y-values for the same X-range
=GROWTH(B1:B10; A1:A10)
Forecast future values
Predict Y for X = 11 to 20:
=GROWTH(B1:B10; A1:A10; A11:A20)
Forecast with intercept forced to 1
=GROWTH(B1:B10; A1:A10; A11:A20; FALSE)
Forecast across sheets
=GROWTH(Sheet1.B1:B50; Sheet2.A1:A50; Sheet2.A51:A60)
Advanced Examples â–¾
Fill missing values in an exponential dataset
=GROWTH(B1:B100; A1:A100; A1:A100)
Multi-variable exponential regression prediction
=GROWTH(Y1:Y20; X1:Z20; X21:Z30)
Predict using LOGEST coefficients (manual equivalent)
Base (m):
=INDEX(LOGEST(B1:B10; A1:A10); 1)
Intercept (b):
=INDEX(LOGEST(B1:B10; A1:A10); 1; 2)
Prediction:
=INDEX(LOGEST(B1:B10; A1:A10); 1; 2) * INDEX(LOGEST(B1:B10; A1:A10); 1) ^ X
GROWTH automates this.
GROWTH ignoring errors
=GROWTH(IF(ISNUMBER(B1:B10); B1:B10); A1:A10; A11:A20)
(Confirm with Ctrl+Shift+Enter in older Calc.)
GROWTH on visible cells only (filtered data)
Use SUBTOTAL helper column to filter X/Y before passing to GROWTH.
GROWTH for time-series forecasting
If A1:A10 contains dates:
=GROWTH(B1:B10; A1:A10; A11:A20)
GROWTH for compounding processes
=GROWTH(Population; Years; FutureYears)
How GROWTH Calculates Predictions â–¾
GROWTH uses the same exponential model as LOGEST:
y = b * m^x
Steps:
- Compute m (growth factor) and b (intercept) using exponential least squares
- For each
new_x, compute:
y = b * m^new_x - Return an array of predicted values
If const = FALSE, the model becomes:
y = m^x
Requirements and Constraints â–¾
- All Y values must be positive
- X values may be any real numbers
- Multi-variable regression requires matching row counts
Common Errors and Fixes â–¾
Err:502 — Invalid argument
Occurs when:
- Y values contain zero or negative numbers
- X and Y ranges have mismatched lengths
- Non-numeric text included
Err:504 — Parameter error
Occurs when:
- Semicolons are incorrect
- Range references malformed
GROWTH returns only one value instead of many
Occurs when:
- Output range too small in older Calc
- Not entered as array formula (older versions)
GROWTH predictions look incorrect
Possible causes:
- Relationship is not exponential
- Outliers distort regression
- Y-values include zeros or negatives
Best Practices â–¾
- Use GROWTH for exponential forecasting and compounding processes
- Use TREND for linear forecasting
- Use LOGEST when you need full regression statistics
- Remove or investigate outliers
- Ensure Y values are strictly positive
- Use named ranges for cleaner formulas
GROWTH is perfect for modeling compounding processes — population growth, financial projections, decay curves, and anything that accelerates or decelerates exponentially.