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Home / Products / S-PLUS®

S+ 8 comprehensive feature list

S PROGRAMMING LANGUAGE
The award-winning S programming language is at the core of S-PLUS. The only language created specifically for exploratory data analysis and statistical modeling, the S programming language allows you to create statistical applications up to five times faster than with other languages.

  • Object-oriented, interpreted 4GL language
  • Interactive exploration and fast prototyping
  • Rich data structures: vector, matrix, array, data frame, list and many more
  • User-defined functions, objects, classes, methods and libraries
  • Library of over 4000 functions for data manipulation, graphics, statistical modeling, and integration
  • CSAN library of available packages

S-PLUS WORKBENCH DEVELOPMENT ENVIRONMENT
Rapidly create reliable statistical applications with this integrated development environment for S programmers.

  • Based on industry-standard Eclipse framework
  • Check-in and check-out files with source code control system integration
  • Intelligent editor for S programs with line numbering, automatic indentation, and syntax highlighting
  • Project, file and task management
  • Automatic syntax error detection
  • Code outline browser
  • Command-line console with history recall
  • Object and search path views
  • Analytic step-by-step debugger
  • Analytic profiling
  • Package system for improved porting and deployment

GRAPHICAL USER INTERFACE
A convenient window-based GUI puts common tasks at your fingertips with easy-to-use menus and dialogs

  • File import and export dialogs
  • Database import and export dialogs¹
  • Dialogs for data preparation, charting and statistical modeling
  • Interactive command-line with history recall
  • Manage objects with Object Explorer¹
  • Script file editor¹
  • Multiple data and graphics windows
  • Cut-and-paste to Word, PowerPoint and Excel¹
  • Integrated Excel spreadsheets¹
  • PowerPoint Wizard: quickly create slides from charts¹
  • Create custom toolbars, menus and dialogs¹
  • On-line help and manuals
  • Eclipse based development environment

SCALABLE PIPELINE ARCHITECTURE
Scale statistical applications to gigabytes of data without the need for additional RAM or 64-bit architectures with this library of data types and functions for programming with large data sets.

  • Data types for out-of-memory vectors, data frames, and time series
  • Use familiar S functions, operators and programming style
  • Scalable algorithms for data manipulation, charting and modeling
  • High-performance data preparation tools: aggregate, merge, sort, partition, filter and more
  • Data manipulation using built-in SQL processor
  • Hexagonal binning plots to explore structure of large data sets
  • Scalable model estimation: univariate statistics, linear regression, analysis of variance, logistic regression, poisson regression, quasi-likelihood, K‑means clustering, principal components
  • Scalable model scoring for more than 20 model types

GRAPHICAL FUNCTIONS
Explore data and create custom charts with this library of graphical functions in the S language

  • Scatterplots, histograms, pie charts, box plots, bar charts, dot charts, time series charts, 3-D wireframe charts, image plots and many more.
  • Brush and spin dynamic visualization
  • Programmatic control over colors, lines, axes, annotations and layout
  • Unique Trellis™ graphics – create multiple charts conditioned by levels of one or more variables
  • Create interactive, embedded web-based charts with S‑PLUS Graphlets™
  • Element-Specific Graph arguments for plots and command-line graphics

INTEGRATION
S-PLUS is an open system, designed to integrate with the systems you already have.

Data and graphics formats

  • ASCII: fixed format, comma-separated, and tab-delimited
  • Spreadsheets: Excel, Lotus 1-2-3, Quattro Pro
  • Application data: SAS 7/8/9, SPSS, Matlab, Minitab, Sigma Plot, Systat, STATA, Gauss, Epi Info and more
  • Database files: Paradox, dBase, Access, FoxPro
  • Financial data sources: LIM, Bloomberg, FAME
  • Native database clients: SQL Server¹, Oracle, Sybase, IBM DB2
  • ODBC interface to compliant databases
  • Export graphics as PDF, PostScript, GIF, PNG, JPG, WMF, bitmap, TIFF and more

APIs and system interfaces

  • APIs for C, C++, Java and Fortran
  • Language support for pipes, sockets, and files
  • DDE, COM and OLE interfaces¹
  • XML import and export
  • Reporting in XML, PDF, HTML and RTF

STATISTICAL & NUMERICAL TECHNIQUES
S-PLUS is the most comprehensive statistical analysis package available, and includes all of the following capabilities:

Basic Statistics

  • Summary statistics
  • Crosstabulations
  • Correlation and covariance
  • Probabilities, quantiles, densities and random number generation from many distributions
  • Durbin-Watson statistic

Hypothesis Tests and Confidence Intervals

  • One-sample and two-sample t-test and Wilcoxon
  • Paired t-test
  • Correlation: Pearson, Kendall's tau, Spearman's rho
  • Goodness-of-Fit: Chi-square, Kolmogorov-Smirnov, Shapiro-Wilk
  • Rank tests: Kruskal-Wallis, Friedman
  • Proportions: exact Binomial test, Normal approximation
  • Contingency tables and tests for independence: Chi-square, Fisher, Mantel-Haenszel, McNemar

Regression

  • Basic linear regression
  • Polynomial regression
  • Model diagnostics
  • Prediction and confidence intervals
  • Stepwise selection of models
  • Parametric spline models
  • Constrained regression
  • Logistic regression
  • Generalized linear models

Analysis of Variance

  • Univariate and multivariate ANOVA
  • Flexible specification of variables, covariables, interactions, nesting, transformations
  • Automatic generation of dummy variables
  • Choice of contrasts
  • Type III sums of squares
  • Designed experiments: one-way, two-way, factorial, split-plot, unbalanced, fractional factorial designs, response surface methods, robust designs, taguchi methods and more
  • Variance component estimation
  • Multiple comparisons: Fisher, Tukey, Dunnett, Sidak, Bonferroni, Scheffé, simulation-based

Nonlinear Regression and Maximum Likelihood

  • Nonlinear regression
  • Nonlinear maximum likelihood
  • Quasi-likelihood
  • Constrained nonlinear regression

Nonparametric Regression

  • Generalized additive models (GAMs)
  • Smoothers: loess, super, kernel, spline
  • Projection Pursuit, ACE, and AVAS

Tree Models

  • Classification trees
  • Regression trees
  • Pruning, shrinking, and splitting
  • Scoring

Correlated Data Analysis

  • Longitudinal data and repeated measures analysis
  • Linear (LME), nonlinear (NLME), and generalized mixed effects (GLMM) models
  • Generalized Estimating Equations (GEE)
  • Biexponential, first-order compartment, four-parameter logistic models
  • User-defined correlation structures

Resampling

  • Bootstrap
  • Jackknife

Multivariate Analysis

  • Canonical correlation
  • Discriminant analysis
  • Factor analysis
  • Multidimensional scaling
  • Principal components
  • Biplots

Cluster Analysis

  • K-means
  • Hierarchical clustering
  • Monothetic clustering
  • Model-based clustering
  • Crisp and fuzzy clustering
  • Divisive and agglomerative methods

Quality Control

  • Shewhart chart
  • Cusum chart
  • Charts based on xbar, s, np, p, c, u

Power and Sample Size

  • Normal mean
  • Binomial proportion

Survival Analysis

  • Kaplan-Meier curves
  • Cox proportional hazards models with mixed effects
  • Left, right, and interval censoring
  • Time-dependent covariates and strata
  • Multiple event models
  • Competing risk models
  • Frailty models
  • Parametric survival
  • Expected survival
  • Person years analysis
  • Aalen's Additive Regression Model

Time Series Analysis

  • Autocovariance, autocorrelation and partial autocorrelation
  • Smoothed periodograms
  • Box-Jenkins ARIMA models
  • Classical and robust AR
  • Long-memory models
  • Seasonal decompositions
  • Fourier transformations
  • Classical and robust smoothers and filters

Robust Statistics

  • Robust estimation and inferences
  • Robust MM regression
  • Robust GLM, ANOVA, covariance, principal components, and discriminant analysis
  • Least trimmed squares regression
  • Minimum absolute residual regression
  • Visually compare robust and traditional methods

Missing Data

  • Multiple imputation
  • Gaussian, logistic, and conditional Gaussian models

Date, Time, and Calendar Data

  • Univariate and multivariate time series
  • Aggregation, alignment, merging, and interpolation
  • Times and dates from milliseconds to millennia
  • Time zones with international daylight savings rules
  • Holidays and financial market closures
  • Custom time and date formats
  • Relative time, time sequence, and event objects
  • Powerful time-series charting

Mathematical Computations

  • Vector and matrix algebra
  • Matrix decompositions
  • Systems of linear equations
  • Locate roots
  • Nonlinear optimization
  • Constrained optimization
  • Ordinary differential equations
  • Numerical integration

ADDITIONAL LIBRARIES
Libraries from Insightful Research and the S‑PLUS user community offer additional capabilities

  • MASS: Modern and Applied Statistics libraries (Venables, Ripley) included
  • Hmisc and Design libraries for biostatistical and epidemiologic modeling (Harrell) included
  • Insightful Research libraries available for download

ADD-ON MODULES
Optional modules add additional capabilities to S+:

  • S+FinMetrics: financial econometrics
  • S+NuOPT: large-scale constrained optimization
  • S+SeqTrial: Clinical trial design and analysis¹

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