Version 6.0.0

June 2012

New Examples

@RISK 6.0 includes a completely revised set of example files, designed and written by leading MBA professor and author Dr. Chris Albright of Indiana University.  There are over 140 example files in all, organized by a range of industry types and applications.  Each includes plain-language descriptions, and may be edited to suit your situation.  In addition, many of the examples include a web link to a short video walk-through of the model.  

New Video Tutorials

New video tutorials have also been added from Dr. Albright.  A new, interactive Quick Start tutorial shows new users how to build and understand a simple simulation model in less than 30 minutes.  In addition, other video tutorial resources have been developed to help experienced users get the most out of their software.

Project Simulation

The features of @RISK for Project are now integrated with the @RISK for Excel interface, allowing you to combine the flexibility of Excel modeling, project scheduling, cost modeling, and Monte-Carlo simulation.

Time Series

@RISK 6.0 has the new ability to create, fit, and simulate time series models, including ARIMA, G/ARCH, and GBM models.

New Fitting Functionality

@RISK contains several important new fitting features, including “Live” fitting functions, parametric bootstrapping for calculating confidence intervals, information criteria measures for model selection, batch fitting, and specification of fixed parameters.

Simplified Ribbon and Mini-Toolbar

The @RISK toolbar ribbon has been better organized to allow quicker access to common tasks, and to make it easier to find different analyses.  @RISK also provides a context enabled mini-toolbar for quick access to graphs and functions.

Combined Graph and Statistics/Data View

@RISK graphs now have a sophisticated split view where both the graph and its corresponding statistics or data can be shown simultaneously.

Double Sided Tornado and Spider Graphs for Displaying Sensitivity Information

The new “double-sided” tornado graph shows an input’s positive and negative impact on actual output statistics, which will often be much easier to understand than regression or correlation coefficients typically used to display sensitivity information.  This same information can also be displayed in a spider graph.

New Distribution Functions

New distribution functions have been added to @RISK, including RiskBernoulli, RiskDoubleTriang, RiskExtValueMin, RiskExtValueMinAlt, RiskF, RiskLaplace, RiskLaplaceAlt, RiskLevy, and RiskLevyAlt.

RISKOptimizer / @RISK Integration

Starting with version 6.0, RISKOptimizer is no longer a separate DecisionTools product, but rather an integrated tool of the @RISK product.  @RISK settings are carried over to RISKOptimizer runs, and @RISK graphs and statistics are displayed with RISKOptimizer optimizations.

OptQuest Optimization Engine Added to RISKOptimizer

The OptQuest optimization engine has been added to RISKOptimizer, providing a powerful alternative to the existing Genetic Algorithm available in previous versions.  RISKOptimizer is able to examine your model and automatically choose which of the engines is most appropriate to optimize it.

With the addition of the OptQuest optimization engine, constraints are often handled more efficiently. If a constraint is linear, RISKOptimizer will not even attempt solutions that fail the constraint, making optimizations faster. The handling of non-linear constraints is also improved. For example, the situation in which an optimization starts with adjustable cell values that do not meet the specified constraints presented a difficulty in previous versions (and required the use of the Constraint Solver utility). With OptQuest this type of situation no longer requires special handling.

Crystal Ball Converter

@RISK can convert Oracle Crystal Ball models into @RISK format.  (Note this converter only works with 32-bit version of Excel, and only if you have an installed, English language version of Crystal Ball.)

New License Manager

A new License Manager has been created to help you view your license information, activate software you have purchased, help you move licenses from one machine to another, and other related tasks.

Other Changes of Note

@RISK Changes

  • Color @RISK Function Cells. @RISK has had the ability to automatically apply color and formatting to the cells that contain @RISK input and output functions since version 5.0.  This feature has been expanded to also include the formatting of @RISK statistic function cells, as well as RISKOptimizer adjustable cells. It also is now directly available from the @RISK ribbon (in Excel 2007 and higher) or @RISK toolbar (in Excel 2003).  In previous versions, this setting could only be found in the @RISK Application Settings dialog.
  • Detailed Statistic Reports.  Excel reports with a large number of inputs and output used to fail with an error message "Report is too large to export to a formatted report - copy and paste data to Excel."  These large reports now will be created in Excel in a “pivoted” form (rows interchanged with columns).
  • Simulation Settings Dialog Defaults. You are now able to write the current settings in the simulation settings dialog directly into the application settings using the button at the bottom of the dialog.
  • Copy From Range in the Simulation Names Dialog.  The simulation names dialog, where you can supply names for multiple simulation runs, now has a button which allows you to copy these names from an Excel spreadsheet range.
  • Fit Results Window “Back” Button.  A new button is available on the Fit Results window to return you to the Fit Definition dialog that created it.  This allows you quickly and easily change the parameters of the fitting process, and then refit.
  • Fitting of RiskPert distributions.  @RISK now can fit RiskPert functions to your data.
  • Suppress Questionable Fits Option.  The new “Suppress Questionable Fits” option controls whether fits that are mathematically valid, but fail one or more meta-mathematical “reality checks” are suppressed.
  • Fitting Defaults in Application Settings.  Default values for many of the options in the Fit Distributions to Data window are now available in the Application Settings dialog.
  • Selectively Remove Tornado Bars.  You can remove a bar from a sensitivity tornado graph by right clicking, and choosing the “Remove Bar” command.
  • Spearman Rank-Order Correlation Coefficient in Scatter Graphs.  @RISK scatter graphs in version 5.0 always displayed the Pearson correlation coefficients between the two variables.  Now in @RISK 6.0, both the Pearson and Spearman Rank correlation coefficients are displayed.
  • Default Target Percentiles for the Detailed Statistics Window in Application Settings.  The bottom section of the @RISK Detailed Statistics Window contains a place where the user can specify one or more custom target percentiles.  These percentiles can now be set by default for all models in the Application Settings window.  This setting is called “Detailed Stats Window Targets” and is in the “Windows” section of the dialog.
  • New API functions for getting model inputs and outputs.  There are two new @RISK API functions, Risk.Model.GetInputFunctions and Risk.Model.GetOutputFunctions for getting a list of the inputs and output functions currently defined in any open Excel workbooks.
  • Improved Support for Multiple CPUs.  New handling of worker CPUs improves the startup and shutdown of multi-cpu simulations.
  • RiskSimulationInfo function returns information about the simulation run, including the number of iterations run, the date and time the simulation was performed, etc.
  • RiskTheoXtoY function returns the probability density or mass function for a theoretical probability distribution function.

RISKOptimizer Changes

  • RISKOptimizer / @RISK Integration.  Starting with version 6.0, RISKOptimizer is no longer a separate DecisionTools product, but rather an integrated tool of the @RISK product.  RISKOptimizer can no longer be launched without launching @RISK.  It no longer has its own Application Settings dialog: instead there is a RISKOptimizer section in @RISK Application Settings dialog.  Also, in RISKOptimizer 5 some simulation settings to be used during optimization were defined in the RISKOptimizer Optimization Settings dialog (for example, the Number of Iterations or "Latin Hypercube" vs. "Monte Carlo" Sampling Type).  In @RISK 6 the same simulation settings are used for simulations that run during a RISKOptimizer optimization and for other @RISK simulations: these are the settings found in @RISK Simulation Settings dialog.
  • RISKOptimizer: "Discrete" adjustable cells.  In previous versions of RISKOptimizer adjustable cells could be defined as taking "Integer" or "Any" values; this selection was performed in the Adjustable Cell Ranges section of the Model dialog in the Values column.  In version 6 there is also an option to define adjustable cell values as "Discrete", and to specify the "Step".  For example, suppose we want to only consider multiples of 10 between 100 and 1000; we can define a Discrete variable with these values as the minimum and the maximum, and 10 as the Step size.  The use of "discrete" adjustable cells reduces dramatically the number of possible solutions compared to adjustable cells for which "Any" values are allowed; this will often result in faster optimizations.  "Discrete" variables are supported with OptQuest, but as of version 6.0.0 they are not supported with the Genetic Algorithm.  With the Genetic Algorithm variables defined as discrete will be treated as non-discrete (after an appropriate warning is displayed).
  • RISKOptimizer: Automatic Constraint Evaluation Time.  When defining some constraints, the user had to specify whether they should be evaluated every iteration, or at the end of a simulation. Now the "Evaluation Time" can be left as "Automatic". In this case if values of constrained cells do not change during a simulation, the constraint will be treated as an iteration constraint; otherwise it will be treated as a simulation constraint.
  • RISKOptimizer: Precision Parameter Added to Constraint Settings Dialog.  The definition of a hard constraint now includes "Precision". This refers to violations of constraints that are so small that RISKOptimizer will disregard them, and will treat a solution as valid despite these small violations. This small imprecision in the handling of constraints relates to the fact that computers can only handle mathematical operations with finite precision. In vast majority of optimizations this setting can be left as "Automatic." With the automatic option, the optimization summary report includes the specific precision value that was selected automatically.
  • RISKOptimizer: Numeric information about constraints provided in the log.  In version 5 the log specified only whether a constraint was met on each trial; in version 6, additional numeric information is provided.  For instance, if we have a constraint saying B3>1000, the log provides the value of cell B3 on each trial.  Note it is not always possible to report the result of the evaluation of a constraint as single number.  For example, consider a constraint saying A1<B1, where both cells are adjusted during optimization; in such cases the program still reports only whether the constraint was met.
  • RISKOptimizer: Reporting complex constraints as individual constraints.  A constraint can be specified in terms of ranges of cells; for example, we may have a constraint saying that A1:A3 < B1:B3.  In version 5 a constraint like that would be reported in one column in the log.  In version 6 it is reported in 3 separate columns (A1<B1, A2<B2, A3<B3), providing more detailed information as to which parts of the original constraint are met, and which ones are not.
  • RISKOptimizer: Constraints with multiple cells and a statistic.  In version 5 it was possible to specify a single constraint saying that A1:A5 < B1:B5 < C1:C5, which said that each cell in the B column was supposed to have a value between the values in the A and the C columns in the same row.  But this method of defining constraints was not available when a statistic was to be constrained, for example when we were interested in the mean or the standard deviation of the cells in column B.  Version 6 adds this functionality, as shown by the Capital Budgeting example.
  • RISKOptimizer: With "Simple" Entry Style, constraint limits no longer need to be fixed values.  In version 5, when defining a constraint with Simple entry style, constraint limits had to be fixed values.  For instance, if A1:C1 were adjustable cells, one could not specify A1>B1>C1 using the "Simple" Entry Style.  The Entry Style had to be changed to "Formula" before the constraint could be entered (and it had to be entered as two separate formulas).  This limitation no longer exists.
  • RISKOptimizer: Support for Excel-defined names.  If a range of cells is named using Excel's interface, RISKOptimizer dialogs and reports will show this name instead of the range address (this applies to workbook-level names, not to worksheet-level names).
  • RISKOptimizer: Single set of genetic algorithm parameters.  This change only affects users with models created with versions of software released before version 6, and only if multiple groups of adjustable cells were defined in the model.  In version 5 it was possible to specify a different mutation rate, crossover rate and genetic operators for each group of adjustable cells.  In version 6 there is one mutation rate, crossover rate and one selection of genetic operators for all adjustable cells.  Models created with version 5 or earlier versions are automatically converted to the new format by version 6.  For example, if different mutation rates are specified for different groups of adjustable cells, after opening with version 6 the same mutation rate will be used for all adjustable cells (and it will be the mutation rate specified for the first group of adjustable cells).  If the workbook is saved and subsequently used with version 5 of the software (or older), then the mutation rate will be set to the same value for all the groups of adjustable cells.

Licensing Changes

  • Ability to Select From Multiple Software Licenses.  In some cases, you may have more than one license for a Palisade product.  For example, if you are employed by a company that gave you a professional license, but also have a student license from a university you attend, there is more than one possible license that could be used.  In version 5.x you were given no choice in this matter; the software would choose one of the licenses for you and proceed to run.  In version 6.x, the Activate License Dialog now allows you to look at all your existing licenses, and choose which one to use.
  • Improved Support for SSD Installations.  New licensing capabilities ease installation and licensing when SSD drives are used.

Important Changes from the @RISK 6.0 Beta

Parameterization of Time-Series AR1, AR2, and ARMA11 Changed From Beta Versions

The parameterization of the new @RISK time-series functions RiskAR1, RiskAR2, and RiskARMA11 have changed slightly since the @RISK beta, so that the parameter μ is now the mean of the (untransformed) process.  If you generated time-series models with the previous beta version, be aware that you may need to adjust your models.

Batch Fit Correlation Calculations

The new @RISK 6.0 batch fitting tools (for both standard distribution fitting and for the fitting of time-series) have been changed from previous beta versions to use Spearman rank-order correlation instead of Pearson coefficients.