SAS/ETS^®

SAS/ETS 15.1 User's Guide - Procedures

• The ARIMA Procedure  PDF   |   HTML
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model.
• The AUTOREG Procedure  PDF   |   HTML
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic.
• The COMPUTAB Procedure  PDF   |   HTML
  Produces tabular reports generated using a programmable data table.
  
• The COPULA Procedure  PDF   |   HTML
  Enables the user to fit multivariate distributions or copulas from a given sample data set.
  
• The COUNTREG Procedure  PDF   |   HTML
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values.
  
• The DATASOURCE Procedure  PDF   |   HTML
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set.
• The ENTROPY Procedure (Experimental)  PDF   |   HTML
  Implements a parametric method of linear estimation based on generalized maximum entropy.
  
• The ESM Procedure  PDF   |   HTML
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data.
• The EXPAND Procedure  PDF   |   HTML
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series.
• The HPCDM Procedure   PDF   |   HTML
  Models compound distributions that are formed by combining models of the frequency of events and the severity of those events.
• The HPCOPULA Procedure  PDF   |   HTML
  Models multivariate distributions by using copula methods.
• The HPCOUNTREG Procedure  PDF   |   HTML
  Fits regression models to analyze and predict counts of the number of events.
• The HPPANEL Procedure  PDF   |   HTML
  Fit regression models to analyze and predict panel data where variables are recorded both over cases and over time.
• The HPQLIM Procedure  PDF   |   HTML
  Fits regression models to analyze and predict qualitative and limited dependent variables where limitations or selection of the observed values must be modeled.
• The HPSEVERITY Procedure  PDF   |   HTML
  Fits regression models to analyze and predict the severity of events by using a variety of probability distributions.
• The LOAN Procedure  PDF   |   HTML
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans.
• The MDC Procedure  PDF   |   HTML
  Analyzes models in which the choice set consists of multiple alternatives.
• The MODEL Procedure  PDF   |   HTML
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations.
• The PANEL Procedure  PDF   |   HTML
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
• The PDLREG Procedure  PDF   |   HTML
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time.
• The QLIM Procedure  PDF   |   HTML
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values.
• The SEVERITY Procedure  PDF   |   HTML
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest.
• The SIMILARITY Procedure  PDF   |   HTML
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data.
• The SIMLIN Procedure  PDF   |   HTML
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure.
• The SPATIALREG Procedure  PDF   |   HTML
  Analyzes spatial econometric models for cross-sectional data whose observations are spatially referenced or georeferenced..
• The SPECTRA Procedure  PDF   |   HTML
  Performs spectral and cross-spectral analysis of time series.
• The SSM Procedure  PDF   |   HTML
  Performs state space modeling of univariate and multivariate time series and longitudinal data.
• The STATESPACE Procedure  PDF   |   HTML
  Uses the state space model to analyze and forecast multivariate time series.
• The SYSLIN Procedure  PDF   |   HTML
  Estimates parameters in an interdependent system of linear regression equations.
• The TIMEDATA Procedure  PDF   |   HTML
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
• The TIMEID Procedure  PDF   |   HTML
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis.
• The TIMESERIES Procedure  PDF   |   HTML
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
• The TMODEL Procedure  PDF   |   HTML   
  Incorporates high-performance computational techniques and offers new features that enhance the functionality of PROC MODEL.
• The TSCSREG Procedure  PDF   |   HTML
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
• The UCM Procedure  PDF   |   HTML
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM).
• The VARMAX Procedure  PDF   |   HTML
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models.
• The X11 Procedure  PDF   |   HTML
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.
• The X12 Procedure  PDF   |   HTML
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.
• The X13 Procedure  PDF   |   HTML
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.

SAS/ETS 14.3 User's Guide - Procedures

• The ARIMA Procedure  PDF   |   HTML
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model.
• The AUTOREG Procedure  PDF   |   HTML
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic.
• The COMPUTAB Procedure  PDF   |   HTML
  Produces tabular reports generated using a programmable data table.
  
• The COPULA Procedure  PDF   |   HTML
  Enables the user to fit multivariate distributions or copulas from a given sample data set.
  
• The COUNTREG Procedure  PDF   |   HTML
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values.
  
• The DATASOURCE Procedure  PDF   |   HTML
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set.
• The ENTROPY Procedure (Experimental)  PDF   |   HTML
  Implements a parametric method of linear estimation based on generalized maximum entropy.
  
• The ESM Procedure  PDF   |   HTML
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data.
• The EXPAND Procedure  PDF   |   HTML
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series.
• The FORECAST Procedure  PDF   |   HTML
  Provides a quick and automatic way to generate forecasts for many time series in one step.
  
• The HPCDM Procedure   PDF   |   HTML
  Models compound distributions that are formed by combining models of the frequency of events and the severity of those events.
• The HPCOPULA Procedure  PDF   |   HTML
  Models multivariate distributions by using copula methods.
• The HPCOUNTREG Procedure  PDF   |   HTML
  Fits regression models to analyze and predict counts of the number of events.
• The HPPANEL Procedure  PDF   |   HTML
  Fit regression models to analyze and predict panel data where variables are recorded both over cases and over time.
• The HPQLIM Procedure  PDF   |   HTML
  Fits regression models to analyze and predict qualitative and limited dependent variables where limitations or selection of the observed values must be modeled.
• The HPSEVERITY Procedure  PDF   |   HTML
  Fits regression models to analyze and predict the severity of events by using a variety of probability distributions.
• The LOAN Procedure  PDF   |   HTML
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans.
• The MDC Procedure  PDF   |   HTML
  Analyzes models in which the choice set consists of multiple alternatives.
• The MODEL Procedure  PDF   |   HTML
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations.
• The PANEL Procedure  PDF   |   HTML
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
• The PDLREG Procedure  PDF   |   HTML
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time.
• The QLIM Procedure  PDF   |   HTML
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values.
• The SEVERITY Procedure  PDF   |   HTML
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest.
• The SIMILARITY Procedure  PDF   |   HTML
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data.
• The SIMLIN Procedure  PDF   |   HTML
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure.
• The SPATIALREG Procedure  PDF   |   HTML
  Analyzes spatial econometric models for cross-sectional data whose observations are spatially referenced or georeferenced..
• The SPECTRA Procedure  PDF   |   HTML
  Performs spectral and cross-spectral analysis of time series.
• The SSM Procedure  PDF   |   HTML
  Performs state space modeling of univariate and multivariate time series and longitudinal data.
• The STATESPACE Procedure  PDF   |   HTML
  Uses the state space model to analyze and forecast multivariate time series.
• The SYSLIN Procedure  PDF   |   HTML
  Estimates parameters in an interdependent system of linear regression equations.
• The TIMEDATA Procedure  PDF   |   HTML
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
• The TIMEID Procedure  PDF   |   HTML
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis.
• The TIMESERIES Procedure  PDF   |   HTML
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
• The TMODEL Procedure  PDF   |   HTML   Experimental
  Incorporates high-performance computational techniques and offers new features that enhance the functionality of PROC MODEL.
• The TSCSREG Procedure  PDF   |   HTML
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
• The UCM Procedure  PDF   |   HTML
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM).
• The VARMAX Procedure  PDF   |   HTML
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models.
• The X11 Procedure  PDF   |   HTML
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
• The X12 Procedure  PDF   |   HTML
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
• The X13 Procedure  PDF   |   HTML
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.

SAS/ETS 14.2 User's Guide - Procedures

• The ARIMA Procedure
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model.
  PDF   |   HTML
• The AUTOREG Procedure
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic.
  PDF   |   HTML
• The COMPUTAB Procedure
  Produces tabular reports generated using a programmable data table.
  PDF   |   HTML
• The COPULA Procedure
  Enables the user to fit multivariate distributions or copulas from a given sample data set.
  PDF   |   HTML
• The COUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values.
  PDF   |   HTML
• The DATASOURCE Procedure
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set.
  PDF   |   HTML
• The ENTROPY Procedure (Experimental)
  Implements a parametric method of linear estimation based on generalized maximum entropy.
  PDF   |   HTML
• The ESM Procedure
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data.
  PDF   |   HTML
• The EXPAND Procedure
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series.
  PDF   |   HTML
• The FORECAST Procedure
  Provides a quick and automatic way to generate forecasts for many time series in one step.
  PDF   |   HTML
• The HPCDM Procedure
  Models compound distributions that are formed by combining models of the frequency of events and the severity of those events.
  PDF   |   HTML
• The HPCOPULA Procedure
  Models multivariate distributions by using copula methods.
  PDF   |   HTML
• The HPCOUNTREG Procedure
  Fits regression models to analyze and predict counts of the number of events.
  PDF   |   HTML
• The HPPANEL Procedure
  Fit regression models to analyze and predict panel data where variables are recorded both over cases and over time.
  PDF   |   HTML
• The HPQLIM Procedure
  Fits regression models to analyze and predict qualitative and limited dependent variables where limitations or selection of the observed values must be modeled.
  PDF   |   HTML
• The HPSEVERITY Procedure
  Fits regression models to analyze and predict the severity of events by using a variety of probability distributions.
  PDF   |   HTML
• The LOAN Procedure
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans.
  PDF   |   HTML
• The MDC Procedure
  Analyzes models in which the choice set consists of multiple alternatives.
  PDF   |   HTML
• The MODEL Procedure
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations.
  PDF   |   HTML
• The PANEL Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
  PDF   |   HTML
• The PDLREG Procedure
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time.
  PDF   |   HTML
• The QLIM Procedure
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values.
  PDF   |   HTML
• The SEVERITY Procedure
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest.
  PDF   |   HTML
• The SIMILARITY Procedure
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data.
  PDF   |   HTML
• The SIMLIN Procedure
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure.
  PDF   |   HTML
• The SPATIALREG Procedure New Procedure!
  Analyzes spatial econometric models for cross-sectional data whose observations are spatially referenced or georeferenced.
  PDF   |   HTML
• The SPECTRA Procedure
  Performs spectral and cross-spectral analysis of time series.
  PDF   |   HTML
• The SSM Procedure
  Performs state space modeling of univariate and multivariate time series and longitudinal data.
  PDF   |   HTML
• The STATESPACE Procedure
  Uses the state space model to analyze and forecast multivariate time series.
  PDF   |   HTML
• The SYSLIN Procedure
  Estimates parameters in an interdependent system of linear regression equations.
  PDF   |   HTML
• The TIMEDATA Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
  PDF   |   HTML
• The TIMEID Procedure
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis.
  PDF   |   HTML
• The TIMESERIES Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
  PDF   |   HTML
• The TSCSREG Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
  PDF   |   HTML
• The UCM Procedure
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM).
  PDF   |   HTML
• The VARMAX Procedure
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models.
  PDF   |   HTML
• The X11 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
  PDF   |   HTML
• The X12 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
  PDF   |   HTML
• The X13 Procedure
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.
  PDF   |   HTML

SAS/ETS 14.1 User's Guide - Procedures

• The ARIMA Procedure
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model.
  PDF   |   HTML
• The AUTOREG Procedure
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic.
  PDF   |   HTML
• The COMPUTAB Procedure
  Produces tabular reports generated using a programmable data table.
  PDF   |   HTML
• The COPULA Procedure
  Enables the user to fit multivariate distributions or copulas from a given sample data set.
  PDF   |   HTML
• The COUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values.
  PDF   |   HTML
• The DATASOURCE Procedure
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set.
  PDF   |   HTML
• The ENTROPY Procedure (Experimental)
  Implements a parametric method of linear estimation based on generalized maximum entropy.
  PDF   |   HTML
• The ESM Procedure
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data.
  PDF   |   HTML
• The EXPAND Procedure
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series.
  PDF   |   HTML
• The FORECAST Procedure
  Provides a quick and automatic way to generate forecasts for many time series in one step.
  PDF   |   HTML
• The HPCDM Procedure
  Models compound distributions that are formed by combining models of the frequency of events and the severity of those events.
  PDF   |   HTML
• The HPCOPULA Procedure
  Models multivariate distributions by using copula methods.
  PDF   |   HTML
• The HPCOUNTREG Procedure
  Fits regression models to analyze and predict counts of the number of events.
  PDF   |   HTML
• The HPPANEL Procedure
  Fit regression models to analyze and predict panel data where variables are recorded both over cases and over time.
  PDF   |   HTML
• The HPQLIM Procedure
  Fits regression models to analyze and predict qualitative and limited dependent variables where limitations or selection of the observed values must be modeled.
  PDF   |   HTML
• The HPSEVERITY Procedure
  Fits regression models to analyze and predict the severity of events by using a variety of probability distributions.
  PDF   |   HTML
• The LOAN Procedure
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans.
  PDF   |   HTML
• The MDC Procedure
  Analyzes models in which the choice set consists of multiple alternatives.
  PDF   |   HTML
• The MODEL Procedure
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations.
  PDF   |   HTML
• The PANEL Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
  PDF   |   HTML
• The PDLREG Procedure
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time.
  PDF   |   HTML
• The QLIM Procedure
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values.
  PDF   |   HTML
• The SEVERITY Procedure
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest.
  PDF   |   HTML
• The SIMILARITY Procedure
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data.
  PDF   |   HTML
• The SIMLIN Procedure
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure.
  PDF   |   HTML
• The SPECTRA Procedure
  Performs spectral and cross-spectral analysis of time series.
  PDF   |   HTML
• The SSM Procedure
  Performs state space modeling of univariate and multivariate time series and longitudinal data.
  PDF   |   HTML
• The STATESPACE Procedure
  Uses the state space model to analyze and forecast multivariate time series.
  PDF   |   HTML
• The SYSLIN Procedure
  Estimates parameters in an interdependent system of linear regression equations.
  PDF   |   HTML
• The TIMEDATA Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
  PDF   |   HTML
• The TIMEID Procedure
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis.
  PDF   |   HTML
• The TIMESERIES Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
  PDF   |   HTML
• The TSCSREG Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
  PDF   |   HTML
• The UCM Procedure
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM).
  PDF   |   HTML
• The VARMAX Procedure
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models.
  PDF   |   HTML
• The X11 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
  PDF   |   HTML
• The X12 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
  PDF   |   HTML
• The X13 Procedure
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.
  PDF   |   HTML

SAS/ETS 13.2 User's Guide - Procedures

• The ARIMA Procedure
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model.
  PDF (9.44MB)  |   HTML
• The AUTOREG Procedure
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic.
  PDF (11.3MB)  |   HTML
• The COMPUTAB Procedure
  Produces tabular reports generated using a programmable data table.
  PDF (3.67MB)  |   HTML
• The COPULA Procedure
  Enables the user to fit multivariate distributions or copulas from a given sample data set.
  PDF (5MB)  |   HTML
• The COUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values.
  PDF (5.52MB)  |   HTML
• The DATASOURCE Procedure
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set.
  PDF (5.08MB)  |   HTML
• The ENTROPY Procedure (Experimental)
  Implements a parametric method of linear estimation based on generalized maximum entropy.
  PDF (5.15MB)  |   HTML
• The ESM Procedure
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data.
  PDF (3.23MB)  |   HTML
• The EXPAND Procedure
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series.
  PDF (3.28MB)  |   HTML
• The FORECAST Procedure
  Provides a quick and automatic way to generate forecasts for many time series in one step.
  PDF (4.44MB)  |   HTML
• The HPCDM Procedure (Experimental)
  Models compound distributions that are formed by combining models of the frequency of events and the severity of those events.
  PDF (5.22MB)  |   HTML
• The HPCOPULA Procedure
  Models multivariate distributions by using copula methods.
  PDF (2.79MB)  |   HTML
• The HPCOUNTREG Procedure
  Fits regression models to analyze and predict counts of the number of events.
  PDF (3.12MB)  |   HTML
• The HPPANEL Procedure
  Fit regression models to analyze and predict panel data where variables are recorded both over cases and over time.
  PDF (2.99MB)  |   HTML
• The HPQLIM Procedure
  Fits regression models to analyze and predict qualitative and limited dependent variables where limitations or selection of the observed values must be modeled.
  PDF (3.88MB)  |   HTML
• The HPSEVERITY Procedure
  Fits regression models to analyze and predict the severity of events by using a variety of probability distributions.
  PDF (8.73MB)  |   HTML
• The LOAN Procedure
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans.
  PDF (4.02MB)  |   HTML
• The MDC Procedure
  Analyzes models in which the choice set consists of multiple alternatives.
  PDF (5.31MB)  |   HTML
• The MODEL Procedure
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations.
  PDF (22.3MB)  |   HTML
• The PANEL Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
  PDF (6.15MB)  |   HTML
• The PDLREG Procedure
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time.
  PDF (3.41MB)  |   HTML
• The QLIM Procedure
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values.
  PDF (6.14MB)  |   HTML
• The SEVERITY Procedure
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest.
  PDF (10.1MB)  |   HTML
• The SIMILARITY Procedure
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data.
  PDF (4.47MB)  |   HTML
• The SIMLIN Procedure
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure.
  PDF (3.78MB)  |   HTML
• The SPECTRA Procedure
  Performs spectral and cross-spectral analysis of time series.
  PDF (3.09MB)  |   HTML
• The SSM Procedure
  Performs state space modeling of univariate and multivariate time series and longitudinal data.
  PDF (11.9MB)  |   HTML
• The STATESPACE Procedure
  Uses the state space model to analyze and forecast multivariate time series.
  PDF (5.39MB)  |   HTML
• The SYSLIN Procedure
  Estimates parameters in an interdependent system of linear regression equations.
  PDF (8.63MB)  |   HTML
• The TIMEDATA Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
  PDF (2.49MB)  |   HTML
• The TIMEID Procedure
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis.
  PDF (3.09MB)  |   HTML
• The TIMESERIES Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format.
  PDF (3.91MB)  |   HTML
• The TSCSREG Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined.
  PDF (2.39MB)  |   HTML
• The UCM Procedure
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM).
  PDF (8.08MB)  |   HTML
• The VARMAX Procedure
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models.
  PDF (10.3MB)  |   HTML
• The X11 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations.
  PDF (3.62MB)  |   HTML
• The X12 Procedure
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations.
  PDF (8.45MB)  |   HTML

SAS/ETS 13.1 User's Guide - Procedures

• The ARIMA Procedure
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model. [HTML]
• The AUTOREG Procedure
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic. [HTML]
• The COMPUTAB Procedure
  Produces tabular reports generated using a programmable data table. [HTML]
• The COPULA Procedure
  Enables the user to fit multivariate distributions or copulas from a given sample data set. [HTML]
• The COUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values. [HTML]
• The DATASOURCE Procedure
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set. [HTML]
• The ENTROPY Procedure (Experimental)
  Implements a parametric method of linear estimation based on generalized maximum entropy. [HTML]
• The ESM Procedure
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data. [HTML]
• The EXPAND Procedure
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series. [HTML]
• The FORECAST Procedure
  Provides a quick and automatic way to generate forecasts for many time series in one step.[HTML]
• The LOAN Procedure
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans. [HTML]
• The MDC Procedure
  Analyzes models in which the choice set consists of multiple alternatives. [HTML]
• The MODEL Procedure
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations. [HTML]
• The PANEL Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined. [HTML]
• The PDLREG Procedure
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time. [HTML]
• The QLIM Procedure
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values. [HTML]
• The SEVERITY Procedure
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest. [HTML]
• The SIMILARITY Procedure
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data. [HTML]
• The SIMLIN Procedure
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure. [HTML]
• The SPECTRA Procedure
  Performs spectral and cross-spectral analysis of time series. [HTML]
• The SSM Procedure
  Performs state space modeling of univariate and multivariate time series and longitudinal data. [HTML]
• The STATESPACE Procedure
  Uses the state space model to analyze and forecast multivariate time series. [HTML]
• The SYSLIN Procedure
  Estimates parameters in an interdependent system of linear regression equations. [HTML]
• The TIMEDATA Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format. [HTML]
• The TIMEID Procedure
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis. [HTML]
• The TIMESERIES Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format. [HTML]
• The TSCSREG Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined. [HTML]
• The UCM Procedure
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM). [HTML]
• The VARMAX Procedure
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models. [HTML]
• The X11 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations. [HTML]
• The X12 Procedure
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations. [HTML]

SAS/ETS 12.3 User's Guide - Procedures

• The ARIMA Procedure
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model. [HTML]
• The AUTOREG Procedure
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic. [HTML]
• The COMPUTAB Procedure
  Produces tabular reports generated using a programmable data table. [HTML]
• The COPULA Procedure
  Enables the user to fit multivariate distributions or copulas from a given sample data set. [HTML]
• The COUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values. [HTML]
• The DATASOURCE Procedure
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set. [HTML]
• The ENTROPY Procedure
  Implements a parametric method of linear estimation based on generalized maximum entropy. [HTML]
• The ESM Procedure
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data. [HTML]
• The EXPAND Procedure
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series. [HTML]
• The FORECAST Procedure
  Provides a quick and automatic way to generate forecasts for many time series in one step.[HTML]
• The LOAN Procedure
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans. [HTML]
• The MDC Procedure
  Analyzes models in which the choice set consists of multiple alternatives. [HTML]
• The MODEL Procedure
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations. [HTML]
• The PANEL Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined. [HTML]
• The PDLREG Procedure
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time. [HTML]
• The QLIM Procedure
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values. [HTML]
• The SEVERITY Procedure
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest. [HTML]
• The SIMILARITY Procedure
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data. [HTML]
• The SIMLIN Procedure
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure. [HTML]
• The SPECTRA Procedure
  Performs spectral and cross-spectral analysis of time series. [HTML]
• The SSM Procedure
  Performs state space modeling of univariate and multivariate time series and longitudinal data. [HTML]
• The STATESPACE Procedure
  Uses the state space model to analyze and forecast multivariate time series. [HTML]
• The SYSLIN Procedure
  Estimates parameters in an interdependent system of linear regression equations. [HTML]
• The TCOUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values. [HTML]
• The TIMEDATA Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format. [HTML]
• The TIMEID Procedure
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis. [HTML]
• The TIMESERIES Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format. [HTML]
• The TSCSREG Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined. [HTML]
• The UCM Procedure
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM). [HTML]
• The VARMAX Procedure
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models. [HTML]
• The X11 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations. [HTML]
• The X12 Procedure
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations. [HTML]

SAS/ETS 9.3 User's Guide - Procedures

For the complete SAS/ETS 9.3 User's Guide, go to the SAS/ETS product documentation page.

• The ARIMA Procedure
  Analyzes and forecasts equally spaced univariate time series data, transfer function data, and intervention data by using the autoregressive integrated moving-average (ARIMA) or autoregressive moving-average (ARMA) model. [HTML]
• The AUTOREG Procedure
  Estimates and forecasts linear regression models for time series data when the errors are autocorrelated or heteroscedastic. [HTML]
• The COMPUTAB Procedure
  Produces tabular reports generated using a programmable data table. [HTML]
• The COPULA Procedure
  Enables the user to fit multivariate distributions or copulas from a given sample data set. [HTML]
• The COUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values. [HTML]
• The DATASOURCE Procedure
  Extracts time series and event data from many different kinds of data files distributed by various data vendors and stores them in a SAS data set. [HTML]
• The ENTROPY Procedure
  Implements a parametric method of linear estimation based on generalized maximum entropy. [HTML]
• The ESM Procedure
  Generates forecasts by using exponential smoothing models with optimized smoothing weights for many time series or transactional data. [HTML]
• The EXPAND Procedure
  Converts time series from one sampling interval or frequency to another and interpolates missing values in time series. [HTML]
• The FORECAST Procedure
  Provides a quick and automatic way to generate forecasts for many time series in one step.[HTML]
• The LOAN Procedure
  Analyzes and compares fixed rate, adjustable rate, buydown, and balloon payment loans. [HTML]
• The MDC Procedure
  Analyzes models in which the choice set consists of multiple alternatives. [HTML]
• The MODEL Procedure
  Analyzes models in which the relationships among the variables comprise a system of one or more nonlinear equations. [HTML]
• The PANEL Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined. [HTML]
• The PDLREG Procedure
  Estimates regression models for time series data in which the effects of some of the regressor variables are distributed across time. [HTML]
• The QLIM Procedure
  Analyzes univariate and multivariate limited dependent variable models in which dependent variables take discrete values or dependent variables are observed only in a limited range of values. [HTML]
• The SEVERITY Procedure
  Estimates parameters of any arbitrary continuous probability distribution that is used to model the magnitude (severity) of a continuous-valued event of interest. [HTML]
• The SIMILARITY Procedure
  Computes similarity measures associated with time-stamped data, time series, and other sequentially ordered numeric data. [HTML]
• The SIMLIN Procedure
  Reads the coefficients for a set of linear structural equations, which are usually produced by the SYSLIN procedure. [HTML]
• The SPECTRA Procedure
  Performs spectral and cross-spectral analysis of time series. [HTML]
• The SSM Procedure
  Performs state space modeling of univariate and multivariate time series and longitudinal data. [HTML]
• The STATESPACE Procedure
  Uses the state space model to analyze and forecast multivariate time series. [HTML]
• The SYSLIN Procedure
  Estimates parameters in an interdependent system of linear regression equations. [HTML]
• The TCOUNTREG Procedure
  Analyzes regression models in which the dependent variable takes nonnegative integer or count values. [HTML]
• The TIMEID Procedure
  Evaluates a variable in an input data set for its suitability as a time ID variable in SAS procedures and solutions that are used for time series analysis. [HTML]
• The TIMESERIES Procedure
  Analyzes time-stamped transactional data with respect to time and accumulates the data into a time series format. [HTML]
• The TSCSREG Procedure
  Analyzes a class of linear econometric models that commonly arise when time series and cross-sectional data are combined. [HTML]
• The UCM Procedure
  Analyzes and forecasts equally spaced univariate time series data by using an unobserved components model (UCM). [HTML]
• The VARMAX Procedure
  Estimates the model parameters and generates forecasts associated with vector autoregressive moving-average processes with exogenous regressors (VARMAX) models. [HTML]
• The X11 Procedure
  Makes additive or multiplicative adjustments and creates an output data set containing the adjusted time series and intermediate calculations. [HTML]
• The X12 Procedure
  Makes additive or multiplicative adjustments and creates an output data set that contains the adjusted time series and intermediate calculations. [HTML]

SAS/ETS 9.22 User's Guide - Procedures

For the complete SAS/ETS 9.22 User's Guide, go to the SAS/ETS product documentation page.

• ARIMA [HTML]
• AUTOREG [HTML]
• COMPUTAB [HTML]
• COUNTREG [HTML]
• DATASOURCE [HTML]
• ENTROPY [HTML]
• ESM [HTML]
• EXPAND [HTML]
• FORECAST [HTML]
• LOAN [HTML]
• MDC [HTML]
• MODEL [HTML]
• PANEL [HTML]
• PDLREG [HTML]
• QLIM [HTML]
• SEVERITY [HTML]
• SIMILARITY [HTML]
• SIMLIN [HTML]
• SPECTRA [HTML]
• STATESPACE [HTML]
• SYSLIN [HTML]
• TIMEID [HTML]
• TIMESERIES [HTML]
• TSCSREG [HTML]
• UCM [HTML]
• VARMAX [HTML]
• X11 [HTML]
• X12 [HTML]