
Summary of MacAnova 4.13 Features
 Variables and operations
 Named real, logical and character vectors, matrices and arrays, plus
structures and graph variables
 Coordinate labels for vectors, matrices and arrays
 Usual arithmetic (+, , *, /,
^ or **) plus modular division (%%) and bit
manipulation (%&, %, %^, %!)
 Most operators and many functions work with structures, allowing
analysis of nonrectangular data sets.
 Descriptive notes can be attached to all variables
 Help
 Online usage summaries and complete help for over 550 topics in 8
automatically searched files
 HTML help you can read in your favorite web browser
 Descriptive statistics
 Means, variances, medians, quartiles, extremes, skewness, kurtosis
 Cross tabs and cell means, variances, standard deviations and
extremes, plus cell covariance matrices for multivariate data.
 Linear and generalized linear models
 A linear model grammar with multiple error terms and shortcuts for
polynomial and periodic regressions
 Up to 96 variables, up to 31 of which can be categorical factors
 "On the fly" transformations of response and predictor variables
 ANOVA, MANOVA and regression with optional weights
 Robust ANOVA and regression
 Logistic, probit and Poisson regression
 Iterative proportional fitting
 Model coefficients, standard errors, contrasts
 Residual plots and macros to summarize residuals
 Branch and bound determination of best subset regression with ability
to force in a subset and save the models selected
 Macros for stepwise regression
 Power and sample size functions for CRD and RBD
 ttests, confidence intervals
 Expected mean squares
 Macro for nonlinear least squares
 Matrix algebra
 Matrix multiplication (operators %*%, %c% and
%C%) and inversion
 Linear equation solution (operators %/% and %\%)
 Eigenvalues and eigenvectors and relative eigenvalues and eigenvectors
 Cholesky, QR and SVD decompositions
 Beaton sweep operator
 Trace, diagonal, determinant, outer products, and other matrix and
vector manipulations
 Permutation of dimensions of matrices and arrays
 Other operations such as Kronecker products and MoorePenrose
inverses are provided as macros
 Time series
 Fast Fourier transforms (maximum prime factor of length is 29)
 Convolution and sums of lagged products
 Forward and backward autoregression and moving average operators
 YuleWalker solver and its inverse
 ACF to partial ACF and its inverse
 Spectrum and crossspectrum analysis, including multitaper
estimation
 Macros for least squares and maximum likelihood estimation of ARIMA
models, including seasonal models
 Macros for HannanRissanen and innovations estimation of ARIMA models
 Macros for computing approximate covariances and variances of
autocorrelations using Bartlett's formula
 Macros to compute the autocovariance function and the spectrum
corresponding to an ARMA model
 Time series plots
 Frequency function plots
 Multivariate analysis
 MANOVA
 Hierarchical cluster analysis
 Kmeans cluster analysis
 Macros related to discrimination and factor analysis, including
stepwise discriminant analysis
 Macros for ULS, GLS and ML factor extraction
 Varimax, quartimax, equimax and orthomax factor rotation
 Design of experiments
 Confounding 2 and 3 series factorials
 Finding aliases in 2 and 3 series fractional factorials
 Choosing generators and design points in 2 series fractional
factorials
 Canonical analysis of 2nd order response surface
 Constrained maximization of quadratic functions
 Recovery of interblock information in incomplete block designs
 REML analysis of unbalanced models with fixed and random terms
 "ANOVA" estimates of random effect variances in mixed effects
 Expectation of mean squares in mixed models
analysis of variance
 Random numbers and probabilities
 Uniform, normal, Poisson and binomial pseudorandom number generators
 Cumulative and inverse normal, chisquare, F, t, beta, gamma
 Cumulative and inverse noncentral chisquare
 Cumulative noncentral F, beta and t
 Cumulative poisson and binomial
 Cumulative and inverse Studentized range
 Cumulative and inverse Dunnett's t
 Graphical features
 Scatter plots, including several y's vs one x
 Line and impulse plots
 Box plots, histograms and stem and leaf displays
 Interaction plots
 Panel graphs, rectangular arrays of small graphs, including
scatterplot matrix
 Contour plots with interactively labelled contours
 Stepwise construction of graphs
 Replotting with changed labels, bounds and tick marks
 Mouse specification of locations for points and lines on a graph
 GRAPH variables encapsulating all the information in a graph
 Graphs are saved when you save your workspace and redrawn when you
restore the workspace
 Transformations
 max, min, sum, prod, all operating on columns of matrices
 Usual transcendentals
 Rational functions (ratios of polynomials)
 Ordering, ranking, sorting
 Importing and exporting data
 Direct importing of data from spreadsheets using the clipboard
 Direct exporting of data and results to other programs using the
clipboard
 Reading and writing named data sets from and to plain text files
 Reading unstructured data together with variable names from plain
text files
 Programmability
 Macros used just like functions
 Many builtin macros plus 8 files of loadable macros (general, time
series, ARIMA modeling, design of experiments, regression,
multivariate analysis, graphics, and mathematics)
 Functions for automatic checking of macro arguments
 Automatic searching for macros that have not yet been loaded
 For and while loops, if, else, elseif, break, next, return
 User functions
 Dynamic loading and execution of user compiled code with callbacks
to MacAnova functions.
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Last modified
Thu Feb 5 12:26:53 CST 2004
