New in ModelRisk Version 5.3

  1. New report types: PDF, MS Word and PowerPoint [All Editions]
  2. Within the ResultsViewer it was always possible to make a report within Microsoft Excel, showing graphs, statistics and tables. ModelRisk 5.3 now has the capability of exporting the results with just two clicks to Microsoft Word, Powerpoint or PDF format. Creating organized, professional looking reports was never so easy and flexible.

  3. Embedded Excel reports [All Editions]
  4. Modelers often embed statistical results in tables within Excel using ModelRisk's statistical functions like VoseSimMean, VoseSimPercentile, etc. For example, one might want to report the probability of exceeding specific planned targets under different possible options. Now those tables of results can be marked with ModelRisk so, at the end of a simulation run, they appear directly within the Results Viewer.

  5. Generalized Pareto Distribution (GPD) [All Editions]
  6. The GPD has applications in the analysis of extreme events with a "long or fat tail", in the modeling of large insurance claims, operational risk, as a failure time distribution and other situations where the Exponential distribution would seem appropriate but gives poor fit to data in its tail. The biggest advantage comes when you fit a spliced distribution to a GPD having a greater possibility of not underestimating the probability of extreme values.

  7. Three Point Estimate Distribution [All Editions]
  8. The simplest subjective estimates (using distributions like Triangle, PERT, Modified PERT) require that one provides minimum, most likely and maximum values for the variable. The minimum and most likely values are usually easy to think about, but the maximum is very often more difficult.

    This distribution replaces the maximum with a percentile, for example the P80 (the value you think there is an 80% chance the variable will not exceed).

  9. Built-in e-learning [All Editions]
  10. ModelRisk now has an extended ribbon that includes different e-learning segments that redirects the user to one of many tutorials, white papers, videos or online training courses. The ribbon also contains a direct search field that searches our extensive help file, containing more than 1200 topics on risk analysis, functions and and basic and advanced risk analysis techniques.

New in ModelRisk Version 5.2

  1. Massive Speed Increase [All Editions]
  2. ModelRisk can now take advantage of the Multi-processor and Multi-core systems in your computer, making Monte Carlo simulations even faster.

  3. Sync All Your Companies Models Together With SIDs [Industrial]
  4. Using SIDs (Simulation Imported Data sets) ensures that all your risk analysis models employ the same stochastic assumptions and forecasts, are consistent, up-to-date, and the results can be rolled up to give a clear and correct assessment of risk for your company as a whole.

  5. Statistical Fit Reports [Industrial]
  6. Clicking the "Create report" button in any of the fitting interfaces (distributions, correlation, and time series) will generate a report in a new worksheet with the fitted models displayed in a table. The table is a complete report of the degree of fit for each model, provides a full statistical comparison with the data, and automatically selects the best fitting model. If you routinely fit the same models to data, you can save this report and reuse it because the report links directly to the data source that can be edited.

  7. Compatible With All Modern Versions Of Excel And Windows [All Editions]
  8. ModelRisk is now fully compatible with the Windows 8 x64 with Excel 2013 x64 system environment.

New in ModelRisk Version 5.1

  1. Precision control functions [All Editions]
  2. A common question people ask is how many samples to run in a Monte Carlo simulation model. The larger the number of samples, the more precisely the output distribution will be known. But how does one set the limit? To make it easier to answer this question, we have added a set of functions that allow the user to ensure that a Monte Carlo simulation has been run with a sufficient number of samples to make sure that a specific level of precision has been achieved.

    With these new functions you can specify the precision required for a cell's mean, standard deviation, the cumulative probability for a specific value or a specific percentile.

  3. Simulation Stop functionality [All Editions]
  4. This function is used to stop a simulation run once a specified condition has been met. When used in conjunction with Precision control functions described above the user can control the length of a simulation run so that it stops when the specified level of precision on statistics for one or more outputs have been achieved. It can also be used if you want to run a model until it generates a particular scenario.

    We have added a special button for the VoseSimStop function on the ModelRisk Ribbon: which switches the functionality on/off.

  5. Model freeze functionality [All Editions]
  6. Sometimes people would like to see the ‘Base’ scenario of the Monte Carlo simulation model – scenario where all random variables are set to their Median values, because it makes it easier to track calculations and compare model versions. For this purpose we have added a new button on the ModelRisk Ribbon that allows removing randomness from the spreadsheet: . Switching the randomness ON/OFF triggers between random sampling from distributions (also Time Series, Copula functions, etc.) and reporting of the Median values.

  7. Time Series [Professional and Industrial Edition]
  8. A set of new Time series models have been added:

    • GBMAJ - A Geometric Brownian Motion time series model with Asymmetric Jumps.
    • GBMVR - A Geometric Brownian Motion time series model with Reversion to a fixed value S
    • GBMAJVR - A Geometric Brownian Motion time series model with Asymmetric Jumps and Reversion to a fixed value S

    All three Time Series models have a standard set of simulation and fitting functions and are available through the Time Series interface windows.

  9. Windows 8 and Microsoft 2013 support [All Editions]
  10. ModelRisk has been updated to run in the most recent operating system from Microsoft – Windows 8 and also the latest spreadsheet modeling environment from Microsoft Excel 2013 is now supported*.

    * System configuration Windows 8 x64bit + Excel 2013 x64bit is not yet supported. The support for this configuration will be released with the next software update.

New in ModelRisk Version 5.0

  1. Improved Results Viewer [All Editions]
  2. A key feature of ModelRisk is the way that simulation results can be viewed and shared with our Results Viewer application. In ModelRisk version 5 we have given the Results Viewer a complete facelift. You are still able to fully customize the graphs and store the results in a separate file that can be reviewed and edited with the free stand-alone Results Viewer application, but with the following improvements:

    • Faster rendering of graphical results
    • A user-friendly ribbon interface that is familiar to everyone who user Microsoft Office products
    • Improved graphics and graphical themes to match the current version of Excel
    • Behavior redesign for an intuitive and easy workflow
    • Multi-document views, allowing viewing and comparing several charts at once
    • Better organization and sorting of model’s inputs and outputs
    • Fully customizable work pane and ribbons

  3. PK/PD (Pharmacokinetic /Pharmacodynamic ) Tool [Industrial Edition]
  4. In conjunction with the clinical pharmacology modeling group of one of the five largest pharmaceutical companies, we have developed a comprehensive PK/PD simulation tool for the pharmaceutical industry. This tool allows the user to build sophisticated PK, PD or PK/PD models that can incorporate uncertainty, variability, and correlation of input parameters and see the results directly in their spreadsheet. The user can select from a library of commonly used models, or define their own models using differential equations. The user can apply a wide variety of dosing options and regimens, see instant graphical results of a simulation and even import model parameters from NONMEM.

  5. Optimal Fit [Professional and Industrial Edition]
  6. ModelRisk already has the capability to fit distributions, correlation structures and time series models to data that will automatically update if the data change. ModelRisk version 5 now includes the ability to choose a set of candidate distributions, etc. to fit to the data and automatically select the optimal-fitting among them directly in your spreadsheet through the OptimalFit set of functions. The result is you can build simpler, transparent and more flexible models around your data. The list of available OptimalFit functions is below:

    • VoseOptimalFit({FittedDistributionObjects}, IC,U) - Returns a random sample from the optimal fitting distribution amongst a set of fitted distributions.
    • VoseCopulaOptimalFit ({FittedCopulaObjects}, IC) - Returns a random sample from the optimal fitting copula amongst a set of fitted copulas.
    • VoseTimeOptimalFit ({FittedTimeSeriesObjects}, IC) - Returns a random sample from the optimal fitting time series model amongst a set of fitted time series models.
    • VoseOptimalFitObject({FittedDistributionObjects}, IC) - Returns the optimal fitting distribution object according to the selected information criteria.
    • VoseCopulaOptimalFitObject ({FittedCopulaObjects}, IC) - Returns the optimal fitting copula object according to the selected information criteria.
    • VoseTimeOptimalFitObject ({FittedTimeSeriesObjects}, IC) - Returns the optimal fitting time series model object according to the selected information criteria.
    • VoseOptimalFitLLH ({FittedObjects}) - Returns the Log Likelihood of the optimal fitting model.
    • VoseOptimalFitAIC ({FittedObjects}) - Returns the Akaike information criteria of the optimal fitting model.
    • VoseOptimalFitHQIC ({FittedObjects}) - Returns the Hannan-Quinn information criteria of the optimal fitting model.
    • VoseOptimalFitSIC ({FittedObjects}) - Returns the Schwarz information criteria of the optimal fitting model.

  7. Extra Database connectivity functions [Industrial Edition]
  8. ModelRisk already offers a powerful feature that allows the user to make live connections to various types of databases, and fit distributions, correlation structures and time series models to these data. Building on this capability, ModelRisk version 5 now also offers a complete list of statistical analyses of the data in these databases directly in the spreadsheet through 12 new functions.

    • VoseDataMean(DataObject) - Returns the mean value of each data column
    • VoseDataStdev(DataObject) - Returns the standard deviation of each data column
    • VoseDataVariance(DataObject) - Returns the variance of each data column
    • VoseDataSkewness(DataObject) - Returns the skewness of each data column
    • VoseDataKurtosis(DataObject) - Returns the kurtosis of each data column
    • VoseDataCofV(DataObject) - Returns the coefficient of variance of each data column
    • VoseDataMoments(DataObject) - Returns the mean, variance, skewness and kurtosis of each data column
    • VoseDataRawMoments(DataObject) - Returns 4 raw moments of each data column
    • VoseDataPercentile(DataObject,Percentile) - Returns the percentile value of each data column
    • VoseDataProbability({x},DataObject,Cumulative) - Returns the probability mass (if Cumulative = FALSE) or cumulative probability (if Cumulative = TRUE) for an array of x-values for each data column
    • VoseDataRowLabel(DataObject) - Returns the array of labels for the referenced data
    • VoseDataSample(DataObject) - Returns a randomly sampled value from each data column

  9. New combined 32-bit/64-bit installation file [All Editions]
  10. A key confusion when installing ModelRisk has been around whether the user has a 32- or 64-bit version of Excel. The ModelRisk installation file now automatically detects the latest version of Excel installed on your machine and selects the appropriate version of ModelRisk to install.


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