SAS/STAT 15.1 Highlights

• NEW! PROC BGLIMM provides full Bayesian inference for generalized linear mixed models (GLMMs).
• NEW! PROC CAUSALGRAPH examines the structure of graphical causal models.
• NEW! PROC RMSTREG analyzes time-to-event data by using regression with respect to the restricted mean survival time (RMST).
• PROC ICPHREG fits the semiparametric proportional hazards model to interval-censored data.
• PROC PHREG performs Bayesian analysis of the proportional hazards spline model.
• PROC QUANTREG enables you to perform observation-wise conditional distribution analysis.

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SAS/QC 15.1 Highlights

SAS/QC 15.1 includes enhancements to several procedures.

• PROC CAPABILITY has the following enhancements:
  • The BARFILL= option in the HISTOGRAM statement enables you to fill the histogram bars in different cells of a comparative histogram with different colors.
  • The PCTLAXIS option in the QQPLOT statement has a new PCTLORDER= suboption, which specifies the tick mark values to be labeled on the percentile axis.
  • In the INTERVALS statement, you can specify METHOD=7 to compute nonparametric tolerance intervals.
• PROC RAREEVENTS enables you to apply tests for special causes to rare events charts. These tests can improve the sensitivity of rare events charts by detecting patterns of measurements that might indicate unusual variation.
• The CCHART, NPCHART, PCHART, and UCHART statements in PROC SHEWHART support the new LANEY option, which computes control limits as recommended by Laney.
• The EWMACHART and MACHART statements in PROC MACONTROL support the new LABASYMPTOTIC option, which labels varying control limits with asymptotic limit values.
• PROC SHEWHART, PROC ANOM, PROC CUSUM, and PROC MACONTROL recognize new macro variables that you can use to control details of ODS Graphics output more conveniently.

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SAS/IML 15.1 Highlights

SAS/IML 15.1 supports several new statements and functions:

• The CONTINUE statement stops the processing of the current iteration of a DO loop and resumes processing at the next iteration of the DO loop.
• The new digital filtering functions enable you to design digital filters and apply those filters to signals. Many of the digital filtering functions start with the "DF" prefix. The new function and subroutines are CCEPSTRUM, DFCONV, DFDESIGN, DFFILT, DFFREQZ, DFFREQZZPK, DFMEDFILT, DFORDER, DFSOSFILT, DFSOSFREQZ, DFSOSFREQZZPK, ICCEPSTRUM, and RCEPSTRUM.
• The experimental KPCATRAIN subroutine computes a kernel principal component (kPCA) analysis from training data. The experimental KCPASCORE function uses the kPCA model to score new data.
• The FEVAL function enables you to evaluate a function indirectly by specifying the name of the function and its arguments.
• The LEAVE statement exits the current DO loop and resumes processing at the statement that follows the DO loop.
• The MODULESTACK function returns the names of all modules in the module call stack.
• The SPECTROGRAM subroutine displays a spectrogram of a short-time Fourier transform of a time series signal.
• The TABLESORT subroutine sorts a table by one or more columns.

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SAS/IML Studio 15.1 Highlights

SAS/IML Studio 15.1 supports the following new features:

• Formats and informats that have been added since SAS 9.2.
• New statements for DO loops. The LEAVE and CONTINUE statements enable you to control when a DO loop terminates or proceeds to the next iteration, respectively.
• New syntax for the FROM keyword of the CREATE and APPEND statements. You can now specify multiple matrices on those statements.

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SAS/OR 15.1 includes performance improvements to its optimization procedures and solvers, including the following enhancements:

• The LP, MILP, network, QP, NLP, and CLP solvers and the decomposition algorithm (for LP and MILP) add performance and stability improvements.
• The LP and MILP solvers significantly reduce their memory consumption.
• The LP solver replaces its presolver.
• The MILP solver and the OPTMILP procedure add the ability to report multiple solutions.
• The network solver adds a path enumeration algorithm to find all paths between specified nodes.
• The connected components algorithm in the OPTNET procedure adds support for the thin internal graph format.
• The DECOMP algorithm adds the COMMUNITY value to the METHOD= option.
• The CLP solver adds the CUMULATIVE predicate, and the CLP procedure adds the CUMULATIVE statement.
• The NLP solver adds a new interior point solution algorithm on an experimental basis.
• The LSO (local search optimization) solver is added and is called by the OPTMODEL procedure.

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SAS Simulation Studio 15.1 adds several enhancements, including the following:

• Improvements in the layout of the graphical user interface (GUI), including collapsible block templates and tabbed project panels
• Easier access to recently opened projects
• The ability to save the size and position of Model and Experiment windows in the last project opened
• Ease-of-use enhancements for models and experiments
• Improved performance in model execution, especially when reading or writing data multiple times
• Authentication during batch mode model runs without the need to open the GUI

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SAS/ETS 15.1 Highlights

SAS/ETS 15.1 includes a new interface engine and enhancements to several procedures:

• SASEOECD interface engine: This new engine enables you to retrieve time series data from the Organisation for Economic Co-operation and Development (OECD) website.
• PROC AUTOREG: The CLASS statement is production, and you can output standard errors of prediction intervals by specifying the STDERR= and STDERRM= options in the OUTPUT statement.
• PROC COPULA: You can use a SIMULATE statement with a BY statement, provided that you specify a FIT statement before the SIMULATE statement. You can also use multiple FIT and SIMULATE statements with a BY statement.
• PROC COUNTREG: This procedure includes two new options for variable selection. The NOSPLITEFFECTS option requests that effects that involve class variables not be split into individual effects that correspond to class levels, and the RETAINEFFECT option requests that the effects named within parentheses be retained during the variable selection process.
• PROC SPATIALREG: Taylor and Chebyshev approximation techniques for spatial error models and spatial Durbin error models have been added.
• PROC SSM: You can now request that parameter estimation be based on a new type of likelihood called marginal likelihood.
• PROC TMODEL: Most features are now production. Only the RANDOM statement and the QUADHESS=ANALYTIC option remain experimental. The LUSOLVER= option has been added to provide better control over the solution of matrix equations that occur in FIT and SOLVE tasks.
• PROC UCM: You can now add a transfer-function component to your model by using the new TF statement. You can also request that parameter estimation be based on a new type of likelihood called marginal likelihood.
• PROC VARMAX: Conditional forecasts and scenario analysis are supported for the vector autoregressive (VAR) model, Bayesian VAR model, vector error correction model (VECM), and Bayesian VECM, with or without exogenous variables. You can now plot dynamic conditional covariances for DCC GARCH models by specifying PLOTS=CONDCORR. The OUTSTAT statement now includes the value of the log-likelihood function that is calculated at the parameter estimates.

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SAS/STAT 14.3 Highlights

• The new CAUSALMED procedure estimates causal mediation effects from observational data.
• The GAMPL procedure now supports the Tweedie distribution.
• In PROC FREQ, the COMMONRISKDIFF option in the TABLES statement provides estimates, confidence limits, and tests for the overall risk (proportion) difference for multiway tables.
• The IRT procedure now supports the nominal response model, which enables you to do item analysis of nominal responses.
• The NLMIXED and MCMC procedures add a CMPTMODEL statement that fits compartment models in pharmacokinetic analysis.
• The PHREG procedure provides the cause-specific proportional hazards analysis for competing-risks data.
• The QUANTREG and QUANTSELECT procedures provide fast quantile process regression.
• The VARMETHOD=BOOTSTRAP option provides variance estimation by the bootstrap method for the survey data analysis procedures.
• The TTEST procedure provides bootstrap standard error, bias estimates, and confidence limits.

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SAS/QC 14.3 Highlights

SAS/QC 14.3 has a new feature for the RAREEVENTS procedure.

In SAS/QC 14.3, the RAREEVENTS procedure can produce rare events charts that have distinct sets of probability limits for different phases of observations. The phases are defined by the values of the character variable _PHASE_ in the data sets that are specified in the DATA=, LIMITS=, and TABLE= options.

The CHART statement supports the following new options related to phases:

• LIMITPHASES= specifies the phases for which probability limits are read from the LIMITS= data set.
• NOPHASEREF suppresses the vertical reference lines that separate phases.
• NOPHASEREFFILL suppresses the filling of graph walls for phases.
• PHASELEGEND displays phase labels in a legend across the top of the chart.
• PHASELIMITS labels probability limits and center lines with their values within each phase.
• READPHASES= selects phases from the DATA= or TABLE= data set for processing.

In addition, you can use the new HAXISLABEL= option in the CHART statement to specify a horizontal axis label for a rare events chart and in the COMPARE statement to specify a horizontal axis label for a comparison chart.

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SAS/IML 14.3 Highlights

• The SAS/IML language supports new syntax for defining and manipulating lists. You can use square brackets to define a list, subscript notation to extract a sublist, a dollar sign ($) to extract an item from a list, and the concatenation operator (||) to concatenate lists. For examples and a description of the syntax, see Lists and Data Structures.
• You can transfer data between SAS/IML tables and R data frames by using the ExportTableToR subroutine and the ImportTableFromR function.
• You can analyze time series data by using the new functions for time-frequency analysis such as the short-time Fourier transform analysis.
• The TABLECREATE function supports creating a table from multiple matrices.
• The SAS/IML wavelet functions now support ODS graphics.

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SAS/OR 14.3 includes performance improvements in the LP, MILP, QP, and NLP solvers. If you also license SAS Optimization 8.1 (or a later release), you can invoke it and SAS/OR 14.3 from the same SAS session.

SAS Simulation Studio 14.3, a component of SAS/OR 14.3 for Windows environments, adds Linux support (on an experimental basis) and also adds an alternative user interface design.

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SAS/ETS 14.3 Highlights

SAS/ETS 14.3 provides the following improvements and enhancements:

• New SASEWBGO interface engine enables you to retrieve time series data from the World Bank Group Open (WBGO) data website.
• New TMODEL procedure incorporates high-performance computational techniques and offers new features that enhance the functionality of PROC MODEL.
• The PANEL procedure was enhanced by adding new options for dynamic panel estimation including DYNDIFF and DYNSYS options to estimate models with differenced and level equations.
• The QLIM procedure adds the no-U-turn sampler (NUTS) of the Hamiltonian algorithm that samples from the posterior distribution by using information from the gradient.
• The SASEFAME interface engine adds features to support remote access to MarketMap's (FAME) master and MCADBS servers.
• The SASEFRED interface engine adds support for USER= and DEBUG= options to store data sets and logs.
• The SASEQUAN interface engine was enhanced to support Version 3 of the Quandl API.
• The SASERAIN interface engine now supports the premium weather API by default while the free weather API has been discontinued by World Weather Online.
• The SSM procedure was enhanced by adding model-based temporal aggregation and temporal distribution for time series that have response variables of flow type.
• The UCM procedure now allows you to specify higher-order stochastic cycle components in your models.
• The VARMAX procedure was enhanced to include support for confidence intervals and standard errors for impulse response functions of exogenous variables and for all impulse response functions of VARFIMA models now appear in corresponding plots and tables.

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SAS/STAT 14.2 Highlights

• The new PSMATCH procedure provides propensity score analysis.
• The new CAUSALTRT procedure performs estimation of causal treatment effects.
• The PHREG procedure now provides time-dependent ROC curves for Cox regression.
• The NLIN procedure now provides ESTIMATE and CONTRAST statements.
• The SURVEYIMPUTE procedure provides two-stage fully efficient fractional imputation and fractional hot-deck imputation.
• The FREQ and SURVEYFREQ procedures provide additional agreement statistics.

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SAS/QC 14.2 Highlights

• The RAREEVENTS procedure is now production. You can compute probability limits based on a Weibull distribution, and the COMPARE statement provides different ways to display the process data and reference distribution.
• The ANOM, CUSUM, MACONTROL, and SHEWHART procedures have new options that provide more flexibility with subgroup markers and labels.

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SAS/IML 14.2 Highlights

• Support for new nonmatrix data types: tables and lists.
  • A table is a rectangular data structure that is an in-memory version of a data set. For more information about tables, see Chapter 9: Mixed-Type Tables
  • A list is a nonrectangular data structure that can contain matrices, tables, and other lists. For more information about lists, see Chapter 10: Lists and Data Structures
• The RANDGEN subroutine supports the following new distributions: Conway-Maxwell-Poisson, extreme value, generalized Poisson, Gompertz, Gumbel, integer, and shifted Gompertz.
• The SUBMIT statement has been enhanced. Macro variables that are created in a SUBMIT block are available outside the SUBMIT block. Global SAS statements that are executed in a SUBMIT block affect the environment outside the SUBMIT block.

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• Performance improvements in the LP, MILP, and NLP optimization solvers and in the decomposition algorithm for LP and MILP
• Better solutions, shorter solution times, and more benchmark problems solved within time limits

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SAS/ETS 14.2 Highlights

• The new SASENOAA interface engine enables you to retrieve severe weather data from the National Oceanic and Atmospheric Administration (NOAA) Severe Weather Data Inventory web service.
• The new SASERAIN interface engine enables you to retrieve weather data from the World Weather Online website, including data on temperature, precipitation (rainfall), weather description, weather icon, and wind speed.
• The new SPATIALREG procedure analyzes spatial econometric models for cross-sectional data that contain spatially referenced or georeferenced observations.
• The HPCDM procedure is now production, with three new options: the MAXCOUNTDRAW= option specifies an upper limit on the number of loss events (count), the SEVERITYSTORE= option specifies the item store that contains the context and estimates of the severity model, and the COUNTSTORE= option supports internal count simulations with BY groups.
• The HPSEVERITY and SEVERITY procedures were enhanced by adding plots for comparative and per-distribution conditional probability density functions. A new OUTPUT statement is available to write distribution function and quantile estimates.
• The QLIM procedure adds the RANDOM statement, which enables you to estimate the random-parameters models in addition to the random-effects models.
• The SASEFAME interface engine was upgraded to support Fame CHLI 11.4.
• The SASEFRED, SASEQUAN, and SASEXFSD interface engines add the CONNECT= option to provide a secure connection via a proxy server, the PROXY= option to specify which proxy server to use, and the DEBUG=ON option to provide diagnostic logging in the SAS log window.
• The SSM procedure adds two options: the new BREAKPEAKS option prints an alternate form of the break summary tables, and the new ZSPARSE option enables the exploitation of the sparsity of the Z_t matrices in the observation equation.
• The TIMESERIES procedure adds the GROUPS= option to allow an automatic grouping based on the w-correlations after a maximal number of groups is specified.
• The VARMAX procedure adds support for vector autoregressive fractionally integrated moving average (VARFIMA) models, which capture both short and long memory in the data and also allow for exogenous variables (VARFIMAX), constants, seasonal dummies, and time trends.

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SAS/STAT 14.1 Highlights

• The new SURVEYIMPUTE procedure provides missing value imputation for survey data.
• The new GAMPL procedure fits generalized additive models via penalized likelihood estimation.
• PROC HPSPLIT provides classification and regression trees via a standard modeling syntax.
• The MCMC procedure adds the Hamiltonian Monte Carlo (HMC) and No-U-Turn Sampler (NUTS) sampling algorithms for continuous parameters, support for leading and lagging variables, an ordinary differential equation solver, and a general integration function.
• The IRT procedure fits generalized partial credit models.
• The LIFETEST procedure performs nonparametric analysis of competing-risks data.
• The POWER procedure supports Cox proportional hazards regression models.

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  • SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data

SAS/QC 14.1 Highlights

• The new, experimental RAREEVENTS procedure produces control charts for rare events. A rare events chart is better suited than traditional control charts to detecting changes in the frequency of low-probability events. The data that are plotted in a rare events chart represent the times between successive events. Rare events charts have gained acceptance in health care quality improvement applications because of their ease of use and suitability to processes that have low defect rates.
• The ANOM, CUSUM, MACONTROL, and SHEWHART procedures are now capable of producing graphs that you can edit by using the ODS Graphics Editor.

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SAS/ETS 14.1 Highlights

• The new X13 procedure incorporates the X12 procedure in response to the US Census Bureau's inclusion of the X-12-ARIMA methodology in the X-13ARIMA-SEATS program. PROC X13 also adds numerous options, displays additional tables, and changes the default value of the MAXITER= option to 1,500.
• The COUNTREG procedure adds the TEST statement, three statements that enable you to include spatial effects in a model, and more Bayesian analysis features.
• The HPCOUNTREG procedure adds the TEST statement and support for the Conway-Maxwell distribution.
• The HPPANEL procedure adds support for the between-groups estimator, between-time-periods estimator, and pooled OLS regression.
• The MODEL procedure adds the %EQAR and %EQMA macros.
• The QLIM procedure adds the RANDOM statement, which enables you to estimate the random-intercept models, and more Bayesian analysis features.
• The SSM procedure adds the DEPLAG statement, which simplifies the specification of models that have lagged values of response variables in the observation equation.

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SAS/STAT 13.2 Highlights

• Weighted generalized estimating equations
• Proportional hazards regression models for interval-censored data
• Spatial point pattern analysis
• Finite mixture models for multinomial data
• Safe screening and sure independence methods for variable selection
• Polychoric correlation matrices, item characteristic curves, and test information curves for IRT models
• Score confidence limits for the odds ratio and the relative risk
• Parameter constraints for nominal response and partial proportional odds models

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SAS/QC 13.2 Highlights

• Geometric means of analysis variables are now computed.
• Confidence bands are available for stress-lifetime plots.
• ODS Graphics output is produced by using templates that are written in the Graph Template Language.

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SAS/ETS 13.2 Highlights

• Convenient access to more than 8 million data sets from the Quandl website
• More Bayesian estimation features in several procedures
• First-differenced methods and new hypothesis tests for panel data
• PROC SEVERITY now supports a CLASS statement and enables you to specify a wide variety of model effects
• Multistep forecasts for multivariate GARCH models and improved cointegration tests in PROC VARMAX
• New options in PROC X12 for forecast confidence limits and outlier detection

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SAS/STAT 13.1 Highlights

• Survival analysis for interval-censored data
• Sensitivity analysis in multiple imputation for missing data
• Item response theory (IRT) models
• Fine and Gray model for competing-risks data
• Bayesian choice models
• Path diagrams for structural equation models

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• Papers
  • Analyzing Interval-Censored Data with the ICLIFETEST Procedure
  • Analyzing Multilevel Models with the GLIMMIX Procedure
  • Creating Path Diagrams That Impress: A New Graphical Capability of the CALIS Procedure
  • Introducing the BCHOICE Procedure for Bayesian Discrete Choice Models
  • Introducing the HPGENSELECT Procedure: Model Selection for Generalized Linear Models and More
  • Is Nonlinear Regression Throwing You a Curve? New Diagnostic and Inference Tools in the NLIN Procedure
  • Item Response Theory: What It Is and How You Can Use the IRT Procedure to Apply It
  • Power and Sample Size for MANOVA and Repeated Measures with the GLMPOWER Procedure
  • SAS/STAT 13.1 Round-Up
  • Sensitivity Analysis in Multiple Imputation for Missing Data
  • Using the PHREG Procedure to Analyze Competing-Risks Data

SAS/IML 13.1 Highlights

• Enhanced linear programming and mixed integer linear programming optimization
• Enhanced data visualization through ODS Graphics
• Additional functions for data analysis and simulation
• New SAS programming window for SAS/IML? Studio
• Enhanced editing features in the SAS/IML Studio programming environment

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SAS Enterprise Miner 13.1 Highlights

• Time series data mining nodes
• Bayesian network classification
• Support vector machines
• Generalized linear models node
• Support for clustered mid-tier deployments
• Model registration

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• Overview
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  • What?s New in SAS Enterprise Miner 13.1
  • Feature Extraction Methods for Time Series Data in SAS Enterprise Miner
  • Link Analysis Using SAS Enterprise Miner
  • Leveraging Ensemble Models in SAS Enterprise Miner
  • An Overview of Machine Learning with SAS Enterprise Miner

SAS/ETS 13.1 Highlights

• Models for limited dependent variables with endogenous regressors
• New multivariate time series techniques that provide performance gains
• Compound distribution modeling for loss simulation
• Multivariate Bayesian limited dependent models
• Convenient access to Federal Reserve Economic Data (FRED)
• Conway-Maxwell-Poisson regression

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• Papers
  • Did My Coupon Campaign Accomplish Anything? An Application of Selection Models to Retailing
  • Simulating Portfolio Losses from Adverse Events: Applications to the Insurance and Finance Industries
  • When Do You Schedule Preventive Maintenance? Multivariate Time Series Analysis in SAS/ETS

SAS Forecast Server 13.1 Highlights

• Diagnostic engine multithreaded for model generation and for variable and event selection
• Forecasting engine multithreaded for model selection
• Support for SAS Grid Manager workspace servers for load balancing of multiple projects
• Interactive exploration and analysis of large volumes of data in SAS Time Series Studio

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  • Ex-Ante Forecast Model Performance with Rolling Simulations
  • High-Performance Forecasting using SAS Grid Manager
  • How to Separate Regular Prices from Promotional Prices?

SAS/STAT 12.1 Highlights

• model selection for quantile regression with the new QUANTSELECT procedure
• quantile regression for censored data with the new QUANTLIFE procedure
• multivariate adaptive regression splines with the new ADAPTIVEREG procedure
• direct and indirect standardized rates and risks for study populations with the new STDRATE procedure
• FMM procedure becomes production and adds support for additional distributions
• Bayesian frailty models in PROC PHREG
• modeling missing covariates in the MCMC procedure
• Mosaic plots and heat maps
• Partial proportional odds model
• Poisson sampling in PROC SURVEYSELECT
• Poststratification estimation in PROC SURVEYMEANS
• Fleming-Harrington estimates in PROC PHREG
• ESTIMATE statement in PROC QUANTREG
• Additional postprocessing inference for the LIFEREG and PROBIT procedures

For More Information

• Overview
• What's New Video
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• Papers
  • Analyzing Survival Data with Competing Risks Using SAS Software
  • Introducing the FMM Procedure for Finite Mixture Models
  • Look Out: After SAS/STAT 9.3 Comes SAS/STAT 12.1!
  • Tips and Strategies for Mixed Modeling with SAS/STAT Procedures
  • Using SAS and LaTeX to Create Documents with Reproducible Results/li>

SAS/IML 12.1 Highlights

• a new syntax for defining default parameter values in user-defined modules
• a new syntax for reading and writing SAS data sets whose names are not known until run time
• new statistical functions, subroutines, and modules
• support for additional distributions and parameters for generating random samples by using the RANDGEN subroutine

In addition, SAS/IML Studio is now available in both a 64-bit edition and a 32-bit edition and supports the following enhancements:

• support for the ODS HTML destination. SAS/IML Studio 12.1 uses the ODS HTML destination by default, which means that you can now view ODS statistical graphics.
• an improved ability to run multiple IMLPlus programs in parallel on computers with multiple processors or with multicore processors
• new method in the R class that enables you to copy plots that are created in R into the ODS HTML or LISTING destination
• support for user-defined formats in data tables and graphs

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SAS Enterprise Miner 12.1 Highlights

• SAS Enterprise Miner Core
  • Several important and common SAS Enterprise Miner project properties have been promoted from macro variables that were deployed by using SAS code or project start code to property selections that can be defined by using the Enterprise Miner GUI properties panel.
  • The SAS Enterprise Miner client can now be opened directly into a specific project or diagram, or from the most recent project and diagram.
  • The %AA_MODEL_REGISTER macro has been added to enable users to directly register models that were developed in SAS code into the SAS Metadata Server. Once in SAS Metadata Server, the common model data can be accessed by SAS products such as SAS Model Manager, SAS Enterprise Guide, and SAS Data Integration Studio.
  • The %AA_MODEL_EVAL macro has been added in order to compute lift and Receiver Operating Characteristic-type measures on any data set that contains probabilities and events. The %AA_MODEL_EVAL macro uses a two-stage approximation algorithm to calculate the model performance measures.
  • Batch code from the SAS Enterprise Miner client can be used more easily with input tables of different names and locations. The SAS Enterprise Miner 12.1 batch code now integrates project start code that you can use to define libraries and options.
  • The SAS Enterprise Miner SAS Code node for version 12.1 contains enhanced support for score code that contains SAS Procedure steps.
  • PMML scoring for the Decision Tree, Regression, Neural Network, and Clustering nodes has been promoted to production status. New experimental functions have been introduced for general regression and scorecards in the SAS Enterprise Miner 12.1 release.
• SAS Enterprise Miner Credit Scoring
  • The Interactive Grouping node user interface has been redesigned to provide improved usability, performance, and computational scalability.
  • The Interactive Grouping node has added a new Calculated variable role.
  • The Scorecard node features an output variable that counts the number of adverse characteristics, and users can select named input variables for adverse characteristic reporting.
  • The Scorecard node now processes indeterminate outcome values.
• SAS Enterprise Miner Applications
  • The Gradient Boosting node now provides users with the capability to disable the H statistic calculation, resulting in improved run-time performance.
  • The Incremental Response node has been promoted from experimental to production status.
  • The Time Series Data Mining nodes have been promoted from experimental to production status. The production Time Series Data Mining nodes have been redesigned to provide greater ease of use as well as improved performance and scalability. It is no longer necessary to precede Time Series Data Mining nodes with a Time Series Data Preparation node. Time series data can now be processed with or without a numeric TimeID variable. Time Series Data Mining now supports sequence data. Season and Trend information is now extracted and included in Time Series Data Mining results.
  • The Decision Tree output displays have been enhanced to display variable precision values in the split branches and nodes. This change improves the usability of the decision tree tool when mining with extremely large and extremely small values.

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  • It?s About Time: Discrete Time Survival Analysis Using SAS Enterprise Miner

SAS/OR 12.1 Highlights

• SAS/OR enables multithreading, employing multiple computational cores on the same computing platform. This has a great impact in several areas of optimization, including problem creation in OPTMODEL, nonlinear multistart optimization, and the new decomposition-based algorithm for linear and mixed integer optimization.
• The OPTMODEL procedure adds a SUBMIT block, which enables you to run other SAS code (including calling other procedures) within PROC OPTMODEL. You can perform analyses, display results, or perform other tasks as integral parts of the process of creating and solving optimization models with PROC OPTMODEL.
• The new OPTNET procedure introduces a versatile set of algorithms for analysis and optimization of network structures (nodes and connecting arcs) that often occur as prominent components of optimization problems.
• SAS Simulation Studio dramatically enhances your ability to work with large models and experiments, introducing new navigational tools, a new search capability, and an alternate Experiment window layout that accommodates large numbers of factors and responses.

For More Information

• Overview
• What's New Chapter
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• Paper
  • Solving Business Problems with SAS Analytics and OPTMODEL
  • New Features in SAS/OR 12.1
  • The Traveling Salesman Traverses the Genome: Using SAS Optimization in JMP Genomics to Build Genetic Maps
  • Bringing Optimization to the Business: Interfacing SAS/OR with SAS Stored Process, Microsoft Excel, SAS Enterprise Guide, SAS Forecast Studio, and Microsoft Project

SAS/ETS 12.1 Highlights

• PROC QLIM now provides users with Bayesian estimation methods for most univariate models supported by the procedure. The QLIM procedure allows users to estimate models of limited dependent variables such as logit/probit, ordered logit/probit, Stochastic frontier, Truncated regression and Censored regression. The main features of the additions include:
  • choosing prior distributions
  • tools to initialize and tune the MCMC algorithm
  • multithreaded Metropolis sampling
  • convergence diagnostic tools
• The PANEL and AUTOREG procedures now offer convenient options to produce variance-covariance matrices for estimates in the presence of heteroscedasticity and/or autocorrelation of unknown form. HAC estimates of standard errors enable OLS estimates to be used for inference despite the presence of heteroscedasticity or autocorrelation.
• A variety of new model specification tests have been added to the PANEL and AUTOREG procedure. These tests are used to check the statistical assumptions of the models, concerning stationarity, cointegration, and structural change. These tests include p-values generated by high performance simulation methods. Many software packages report only selected critical values for these tests.
• Many new ODS plots have been included with the SAS/ETS 12.1 release, including:
  • Predictive and diagnostic plots for PROC COUNTREG
  • Predictive and diagnostic plots for PROC QLIM including Bayesian plots
  • Q-Q Plot for PROC SEVERITY
  • Residual and structural break analysis in PROC SSM
  • Dependency plots in PROC MODEL

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  • Let Oil and Gas Talk to You: Predicting Production Performance