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@RISK for Excel - Industrial

SKU: PAL10CSL

@RISK Industrial Includes Monte-Carlo simulation, distribution fitting, time-series fitting and optimization functionalities. New in version 7 is the ability to build efficient frontiers, use copulas and a host of usability enhancements.

$2,295.00
$2,180.25
Products specifications
Min. OS Requirement Windows XP
Language 6 languages (EN, FR, JP, ES, CN, KR)
Add-In Requires Excel
Available for Mac No, requires Parallels Emulation
Price includes 1st year maintenance
Requires other Software? Requires Microsoft Excel to run
Scripting Support Built In
Simulation Monte Carlo
VBA Support Built In
CSV Support
XML Support
Distribution Fitting Built In
User Defined Distributions
Distribution Gallery 48 base distributions (38 Continuous + 10 Discrete) with 20 that can have alternate parameters
Monte Carlo Sampling
Latin HyperCube Sampling
Process Capability (6 Sigma)
Sensitivity Analysis
Tornado Analysis
Precision Control
Probability calculations functions
Correlation
Correlation Methods Normal Copula Only (Iman- Conover)
SIP Math Support
Decision Trees Requires 3rd party option
Stats Tools We recommend Palisade StatsTools
MS Project Support
Charting Built In
Charts can be customized
Automated Reporting
Multi-Core Support
Developper Kit
Example Models
Network Licensing Available
Data Base Integration 30+ Data Sources with CDATA Connectors
Supported DBs Standard ODBC sources from Excel + 3rd party connectors
User Defined Distribution Library Distributions can be generated and saved to an SQL or SQL Express DB and can be made available to other @RISK users who have access to the repository
Time Series as distributions
Time Series Fitting
Time Series Methods 11 Methods (AutoRegression, GBM, Moving Average)
Multiple Linear Regression Provided using Palisade StatTools
Seasonal Methods Seasonal ARMA & GBM
Non-Seasonal Methods AR(1&2), MA(1&2)
GBM Support Univariate, Multivariate and Seasonal
Cubic Spline
Heteroscedastic Models ARCH, GARCH11, EGARCH11 and APARCH11
ARIMA Support Partial Support for ARMA
AutoARIMA
Data Sensoring Automatic
Time-Series Event Support
Define Time Series All available methods can be configured manually using parameters
Markov Chains
Automatic Data Transform
Manual Data Transform Methods
Manual Deseasonalization
Manual Detrending
Visualize Simulated Output
Exception Reporting
Time Series Scenario Analysis
Error Measures
Time Series Fit Criteria Akaike and Baysean Information Criteria
Product description

@RISK Simulation and Optimization Add-In for Excel

 

@RISK is a complete risk analysis & optimization solution for Excel that allows for the best decision making under uncertainty.

@RISK analyzes thousands of different possible outcomes, showing you the likelihood of each occurring. Uncertain factors are defined using over 35 probability distribution functions, which accurate describe the possible range of values your inputs could take. @RISK 6.x is fully compatible with 64-bit Excel 2010. 64-bit technology enables Excel and @RISK to access much more computer memory than ever before. This allows for vastly larger models and greater computational power. In addition, @RISK has been fully translated into Spanish, German, French, Portuguese, Japanese and .

New in @RISK 6.x

New @RISK version 6.x includes a wide range of improvements, including powerful new integration with Microsoft Project that allows you to perform risk analysis and Monte Carlo simulation on your Microsoft Project schedules – all from the @RISK for Excel platform! Other new features include easier-to-understand tornado charts, better graphing options, improved distribution fitting, new distribution functions, and much more. The Industrial edition now adds the OptQuest solving engine to RISKOptimizer, and features simulation of time-series forecasts.

Integration with Microsoft Project

The new version of @RISK for Excel integrates with Microsoft Project, allowing you to perform all your risk modeling from the more flexible Excel environment. @RISK now imports your Project schedules into Excel so that you can use all of Excel’s formulas, and @RISK’s features, on your Project models. Excel becomes a front-end for your Microsoft Project schedule, linking directly to the underlying .MPP(X) file. Changes made in either Project or Excel are reflected in the other. When it’s time to run your Monte Carlo simulation, Microsoft Project’s scheduling engine is used for the calculations, ensuring accuracy.

Time Series Simulation

@RISK now offers a new set of functions for simulating time series processes, or values that change over time. Any future projection of time series values has inherent uncertainty, and @RISK now lets you account for that uncertainty by looking at the whole range of possible time series projections in your model. This is particularly useful in financial modeling and portfolio simulation.

@RISK for Six Sigma

 

A key application of @RISK is Six Sigma and quality analysis. Industries ranging from engine manufacturing to precious metals to airlines and consumer goods are using @RISK every day to improve their processes, enhance the quality of their products and services, and save money.

Whether it’s in DMAIC, Design for Six Sigma (DFSS), Lean projects, Design of Experiments (DOE), or other areas, uncertainty and variability lie at the core of any Six Sigma analysis. @RISK uses Monte Carlo simulation to identify, measure, and root out the causes of variability in your production and service processes and designs.

Six Sigma Capability Metrics in @RISK

@RISK allows you to define Upper and Lower Specification Limits and Target values for each output, and comes complete with a wide range of Six Sigma statistics and capability metrics on those outputs, like Cpk, Cp, Cpm, and much more. These metrics can be placed directly in your spreadsheet model, or appear in the @RISK Results Summary window. Output graphs show markers for LSL, USL, and Target values. The Industrial edition of @RISK adds RISKOptimizer to your Six Sigma analyses for optimization of project selection, resource allocation, and more.

 

Additional information
Products specifications
Min. OS Requirement Windows XP
Language 6 languages (EN, FR, JP, ES, CN, KR)
Add-In Requires Excel
Available for Mac No, requires Parallels Emulation
Price includes 1st year maintenance
Requires other Software? Requires Microsoft Excel to run
Scripting Support Built In
Simulation Monte Carlo
VBA Support Built In
CSV Support
XML Support
Distribution Fitting Built In
User Defined Distributions
Distribution Gallery 48 base distributions (38 Continuous + 10 Discrete) with 20 that can have alternate parameters
Monte Carlo Sampling
Latin HyperCube Sampling
Process Capability (6 Sigma)
Sensitivity Analysis
Tornado Analysis
Precision Control
Probability calculations functions
Correlation
Correlation Methods Normal Copula Only (Iman- Conover)
SIP Math Support
Decision Trees Requires 3rd party option
Stats Tools We recommend Palisade StatsTools
MS Project Support
Charting Built In
Charts can be customized
Automated Reporting
Multi-Core Support
Developper Kit
Example Models
Network Licensing Available
Data Base Integration 30+ Data Sources with CDATA Connectors
Supported DBs Standard ODBC sources from Excel + 3rd party connectors
User Defined Distribution Library Distributions can be generated and saved to an SQL or SQL Express DB and can be made available to other @RISK users who have access to the repository
Time Series as distributions
Time Series Fitting
Time Series Methods 11 Methods (AutoRegression, GBM, Moving Average)
Multiple Linear Regression Provided using Palisade StatTools
Seasonal Methods Seasonal ARMA & GBM
Non-Seasonal Methods AR(1&2), MA(1&2)
GBM Support Univariate, Multivariate and Seasonal
Cubic Spline
Heteroscedastic Models ARCH, GARCH11, EGARCH11 and APARCH11
ARIMA Support Partial Support for ARMA
AutoARIMA
Data Sensoring Automatic
Time-Series Event Support
Define Time Series All available methods can be configured manually using parameters
Markov Chains
Automatic Data Transform
Manual Data Transform Methods
Manual Deseasonalization
Manual Detrending
Visualize Simulated Output
Exception Reporting
Time Series Scenario Analysis
Error Measures
Time Series Fit Criteria Akaike and Baysean Information Criteria