October 2012
Beginner to intermediate
721 pages
21h 38m
English
This is the main package of Venables and Ripley’s MASS.
| Function | Description |
|---|---|
| Null | Given a matrix M, finds a matrix N giving a basis for the null space.
That is, t(N) \%*\% M is the
0, and N has the maximum
number of linearly independent columns. |
| Shepard | One form of nonmetric multidimensional scaling. |
| addterm | Tries fitting all models that differ from the current model by adding a single term from those supplied, maintaining marginality. |
| area | Integrates a function of one variable over a finite range using a recursive adaptive method. This function is mainly for demonstration purposes. |
| as.fractions | Finds rational approximations to the components of a real numeric object using a standard continued fraction method. |
| bandwidth.nrd | A well-supported rule of thumb for choosing the bandwidth of a Gaussian kernel density estimator. |
| bcv | Uses biased cross-validation to select the bandwidth of a Gaussian kernel density estimator. |
| boxcox | Computes and optionally plots profile log-likelihoods for the parameter of the Box-Cox power transformation. |
| con2tr | Converts lists to data frames for use by lattice. |
| contr.sdif | A coding for unordered factors based on successive differences. |
| corresp | Finds the principal canonical correlation and corresponding row and column scores from a correspondence analysis of a two-way contingency table. |
| cov.mcd, cov.mve, cov.rob | Compute a multivariate location and scale estimate with a high breakdown point. This can be thought of as estimating the mean and covariance of the good part of ... |
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