https://bugs.freedesktop.org/show_bug.cgi?id=87790
--- Comment #6 from mencaraglia <[email protected]> --- What I expect is 0,7364; In these days ha have done some other checks; using the spreadsheet GNUMERIC for instance I find for r2 the value 0,98.... (same as libreoffice); same value using the Google sheet. Using the spreadsheet SCIDAVIS the R2 is 0,73..., Using the program GRETL the results are 0.98... if I use the ordinary least square methd (fit function a *x ) and I find 0,73.... if I use the non linear fit (fit funztion a * x). Looking for other occurrences of the R2 problem (google may help) I found that several years ago ( 2006 ) the same problem (wrong values of r2) had been found for excel and the origin was in the linest() function. see for instance http://support.microsoft.com/kb/829249 I have not worked any more on the subject since (a) i had a work around and (b) it's the first time I fit with Y = a *x and probably next time will be in 10 years (;-) ) Here below please find the two results obtained from GRETL and the one from SCIDAVIS Modello 1: OLS, usando le osservazioni 1-50 Variabile dipendente: v2 coefficiente errore std. rapporto t p-value ------------------------------------------------------------- v1 −1,21416 0,0195447 −62,12 2,91e-48 *** Media var. dipendente −3,693268 SQM var. dipendente 0,833732 Somma quadr. residui 8,977973 E.S. della regressione 0,428047 R-quadro 0,987462 R-quadro corretto 0,987462 F(1, 49) 3859,178 P-value(F) 2,91e-48 Log-verosimiglianza −28,01571 Criterio di Akaike 58,03141 Criterio di Schwarz 59,94343 Hannan-Quinn 58,75952 Note: SQM = scarto quadratico medio; E.S. = errore standard ---------------------------------- Sono state usate derivate analitiche Tolleranza = 1,81899e-12 Convergenza raggiunta dopo 4 iterazioni Modello 2: NLS, usando le osservazioni 1-50 v2 = alpha * v1 stima errore std. rapporto t p-value --------------------------------------------------------- alpha −1,21416 0,0195447 −62,12 2,91e-48 *** Media var. dipendente −3,693268 SQM var. dipendente 0,833732 Somma quadr. residui 8,977973 E.S. della regressione 0,428047 R-quadro 0,736410 R-quadro corretto 0,736410 Log-verosimiglianza −28,01571 Criterio di Akaike 58,03141 Criterio di Schwarz 59,94343 Hannan-Quinn 58,75952 Note: SQM = scarto quadratico medio; E.S. = errore standard ---------------------------------------------------- [02/01/15 14:31 Plot: ''Graph1''] Non-linear fit of dataset: Table1_2, using function: a*x Y standard errors: Unknown Scaled Levenberg-Marquardt algorithm with tolerance = 0,0001 >From x = 0 to x = 3,912 a = -1,21415873230445 +/- 0,0195446571501494 -------------------------------------------------------------------------------------- Chi^2/doF = 0,183223940915315 R^2 = 0,736410071654573 --------------------------------------------------------------------------------------- Iterations = 1 Status = success --------------------------------------------------------------------------------------- -- You are receiving this mail because: You are the assignee for the bug.
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