Hi, I just read the "Embedding R in Gnumeric" idea at http://www.r-project.org/SoC08/ideas.html. On my side, I intend to add as many statistics related plot types to the current gnumeric charting engine as possible. We already have boxplots and partial support for histograms. My immediate plans are to finish the histogram code and add probability plots (http://bugzilla.gnome.org/show_bug.cgi?id=500168) during the summer if time permits (importing some code from R). For the future, I see two options: either add all necessary plot types to the gnumeric charting engine or embedding R charts directly using either a new SheetObject class or the goffice component system (which would allow inserting these charts in abiword as well).
One other totally unrelated thing. We got recently a bug report about an incorrect R squared in gnumeric regression code (http://bugzilla.gnome.org/show_bug.cgi?id=534659). R (version 2.7.0) give the same result as Gnumeric as can be seen below: > mydata <- read.csv(file="data.csv",sep=",") > mydata X Y 1 1 2 2 2 4 3 3 5 4 4 8 5 5 0 6 6 7 7 7 8 8 8 9 9 9 10 > summary(lm(mydata$Y~mydata$X)) Call: lm(formula = mydata$Y ~ mydata$X) Residuals: Min 1Q Median 3Q Max -5.8889 0.2444 0.5111 0.7111 2.9778 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.5556 1.8587 0.837 0.4303 mydata$X 0.8667 0.3303 2.624 0.0342 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 2.559 on 7 degrees of freedom Multiple R-squared: 0.4958, Adjusted R-squared: 0.4238 F-statistic: 6.885 on 1 and 7 DF, p-value: 0.03422 > summary(lm(mydata$Y~mydata$X-1)) Call: lm(formula = mydata$Y ~ mydata$X - 1) Residuals: Min 1Q Median 3Q Max -5.5614 0.1018 0.3263 1.6632 3.5509 Coefficients: Estimate Std. Error t value Pr(>|t|) mydata$X 1.1123 0.1487 7.481 7.06e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 2.51 on 8 degrees of freedom Multiple R-squared: 0.8749, Adjusted R-squared: 0.8593 F-statistic: 55.96 on 1 and 8 DF, p-value: 7.056e-05 I am unable to figure out what this 0.8749 value might represent. If it is intended to be the Pearson moment, it should be 0.4958, and if it is the coefficient of determination, I think the correct value would be 0.4454 as given by Excel. It's of course nice to have the same result in R and Gnumeric,but it would be better if this result was accurate (if it is, we need some documentation fix). Btw, I am not a statistics expert at all. Best regards, Jean Brefort ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
