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SAS/ETS

SAS/ETS User's Guide - Procedures

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SAS/ETS 12.1 User's Guide - Procedures

For the complete SAS/ETS 12.1 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
    Wstimates 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]

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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
    Wstimates 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]

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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.