Appendix B - Brief Description of S-PLUS Subroutines Used in this Book

Summary

General routines such as “log”, “print” etc. are omitted. Arguments set at the default values are not displayed. For a complete description, see the language reference section in S-PLUS.

1. anova(Model) Compute an ANOVA table for Model

2. anova(Model1, Model2, test=“F”) Compare Model1 and Model2

3. aov(formula, data =) Fit an analysis of variance model using formula on data

4. as.numeric(x) returns a vector like x, but with storage mode “double,” if x is a simple object of mode “numeric.” Otherwise, as.numeric returns a numeric object of the same length as x and with data resulting from coercing the elements of x to mode “numeric.”

5. bootstrap(data = statistic, B = trace = F) Performs bootstrap for observations in data = using the statistic specified by statistic. The number of replicates is B and trace determines printing of replicate number during computation.

6. by(X, Indices, function) Split dataset X by Indices and apply function to each part.

7. c Concatenates objects into a vector or a list (e.g., c(0.5, 0.2)).

8. cbind() Returns a matrix that is pieced together, column-wise, from several vectors and/or matrices.

9. ceiling() Creates integers from floating point numbers by going to the next larger integer.

10. chisq.test(x, correct = F) Chi-square contingency test using x. Apply Yates correction if correct = T

11. choose(n, k) Is the binomial coefficients, n!/(k!(n−k)!)

12. contourplot(Z ∼ X*Y, data=, at=0, xlab=“X”, ylab=“Y”) Contour plot of Z on X, Y. In above example, a single contour line of zero (at=0) is drawn.

13. convert.col.type(target = X, column.spec =, column.type =) Converts column(s), column.spec, in a 1- or 2-dimensional dataset, X, to a particular data type, column.type.

14. cor(X, Y, na.method = “omit”) Returns the correlation of a vector or the correlation matrix of a data matrix. Missing values can be omitted or the calculation set to “fail.”

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