Difference between revisions of "Example Models and Libraries - Table"

Line 418: Line 418:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Expected R&D Project Value]]
 
|-
 
|-
  
Line 426: Line 426:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Financial Statement Templates]]
 
|-
 
|-
  
Line 434: Line 434:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Market Model]]
 
|-
 
|-
  
Line 442: Line 442:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Plan_Schedule_ Control]]
 
|-
 
|-
  
Line 450: Line 450:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Project Portfolio Planner]]
 
|-
 
|-
  
Line 458: Line 458:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Sales Effectiveness]]
 
|-
 
|-
  
Line 466: Line 466:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Subscriber Pricing]]
 
|-
 
|-
  
Line 474: Line 474:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Waterfall chart]]
 
|-
 
|-
  
Line 482: Line 482:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Bootstrapping]]
 
|-
 
|-
  
Line 490: Line 490:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Kmeans Clustering]]
 
|-
 
|-
  
Line 498: Line 498:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Logistic regression prior selection]]
 
|-
 
|-
  
Line 506: Line 506:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Moving Average Example]]
 
|-
 
|-
  
Line 514: Line 514:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Multidimensional Scaling]]
 
|-
 
|-
  
Line 522: Line 522:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Principle Components]]
 
|-
 
|-
  
Line 530: Line 530:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Regression Examples]]
 
|-
 
|-
  
Line 538: Line 538:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Two Branch Party Tree]]
 
|-
 
|-
  
Line 546: Line 546:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Beta Updating]]
 
|-
 
|-
  
Line 554: Line 554:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Biotech R&D Portfolio]]
 
|-
 
|-
  
Line 562: Line 562:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Diversification Illustration]]
 
|-
 
|-
  
Line 570: Line 570:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Expected Value of Sampling Information (EVSI)]]
 
|-
 
|-
  
Line 578: Line 578:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Gibbs Sampling in Bayesian Network]]
 
|-
 
|-
  
Line 586: Line 586:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[LEV R&D Strategy]]
 
|-
 
|-
  
Line 594: Line 594:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Marginal Analysis for Control of SO2 Emissions]]
 
|-
 
|-
  
Line 602: Line 602:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Multi-attribute Utility Analysis]]
 
|-
 
|-
  
Line 610: Line 610:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Newton-Raphson Method]]
 
|-
 
|-
  
Line 618: Line 618:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Nonsymmetric Tree]]
 
|-
 
|-
  
Line 626: Line 626:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Party With Forecast]]
 
|-
 
|-
  
Line 634: Line 634:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Plane catching decision with EVIU]]
 
|-
 
|-
  
Line 642: Line 642:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Probability of Gaussian Region (Importance Sampling)]]
 
|-
 
|-
  
Line 650: Line 650:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Supply and Demand]]
 
|-
 
|-
  
Line 658: Line 658:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Tornado Diagrams]]
 
|-
 
|-
  
Line 666: Line 666:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Upgrade Decision]]
 
|-
 
|-
  
Line 674: Line 674:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Disease establishment]]
 
|-
 
|-
  
Line 682: Line 682:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Leveling]]
 
|-
 
|-
  
Line 690: Line 690:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Markov Chain]]
 
|-
 
|-
  
Line 698: Line 698:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Mass-Spring-Damper]]
 
|-
 
|-
  
Line 706: Line 706:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Mean-reversion trading]]
 
|-
 
|-
  
Line 714: Line 714:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Minimal edit distance]]
 
|-
 
|-
  
Line 722: Line 722:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Optimal Path Dynamic Programming]]
 
|-
 
|-
  
Line 730: Line 730:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Parking Space Selection]]
 
|-
 
|-
  
Line 738: Line 738:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Projectile Motion]]
 
|-
 
|-
  
Line 746: Line 746:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Tunnel through earth]]
 
|-
 
|-
  
Line 754: Line 754:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Unequal time steps]]
 
|-
 
|-
  
Line 761: Line 761:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Curve fits noisy time-sequence data using an adaptive filter.</div>
|[[]]
+
|[[Adaptive Filter]]
 
|-
 
|-
  
Line 769: Line 769:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Calculates the expected gain of an antenna looking at two different satellites.</div>
|[[]]
+
|[[Antenna Gain]]
 
|-
 
|-
  
Line 777: Line 777:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Computes the load that a Douglas-Fir Large compression post can support.</div>
|[[]]
+
|[[Compression Post Load Capacity]]
 
|-
 
|-
  
Line 785: Line 785:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Demonstration showing how to analyze life cycle costs and savings from daylighting options in building design.</div>
|[[]]
+
|[[Daylight Analyzer]]
 
|-
 
|-
  
Line 794: Line 794:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Failure Analysis]]
 
|-
 
|-
  
Line 802: Line 802:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Ideal Gas Law]]
 
|-
 
|-
  
Line 810: Line 810:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Power dispatch]]
 
|-
 
|-
  
Line 818: Line 818:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Regular polygon calculator]]
 
|-
 
|-
  
Line 826: Line 826:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Find Words Game]]
 
|-
 
|-
  
Line 834: Line 834:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Fractals everywhere]]
 
|-
 
|-
  
Line 842: Line 842:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Probability assessment]]
 
|-
 
|-
  
Line 850: Line 850:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Abstracted Subset]]
 
|-
 
|-
  
Line 858: Line 858:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Assignment from Button]]
 
|-
 
|-
  
Line 865: Line 865:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Calculates the auto-correlation coefficients of noisy time sequence data.</div>
|[[]]
+
|[[Autocorrelation]]
 
|-
 
|-
  
Line 874: Line 874:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Choice and Determtables]]
 
|-
 
|-
  
Line 882: Line 882:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Correlated Distributions]]
 
|-
 
|-
  
Line 890: Line 890:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Correlated Normals]]
 
|-
 
|-
  
Line 898: Line 898:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[DBWrite Example]]
 
|-
 
|-
  
Line 906: Line 906:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Discrete Sampling]]
 
|-
 
|-
  
Line 913: Line 913:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Demonstrates how to extract a diagonal from a matrix.</div>
|[[]]
+
|[[Extracting Diagonal]]
 
|-
 
|-
  
Line 922: Line 922:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Lookup Reindexing]]
 
|-
 
|-
  
Line 930: Line 930:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Map images from internet]]
 
|-
 
|-
  
Line 938: Line 938:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Sample Size Input Node]]
 
|-
 
|-
  
Line 946: Line 946:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Sorting People by Height]]
 
|-
 
|-
  
Line 953: Line 953:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Creates a subset array out of a larger array based on a decision criterion.</div>
|[[]]
+
|[[Subset of Array]]
 
|-
 
|-
  
Line 961: Line 961:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Swaps a computed or one-dimensional table value with its index, thereby making the computed value an index.</div>
|[[]]
+
|[[Swapping y and x-index]]
 
|-
 
|-
  
Line 970: Line 970:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Use of MDTable]]
 
|-
 
|-
  
Line 978: Line 978:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Airline NLP]]
 
|-
 
|-
  
Line 986: Line 986:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Asset allocation]]
 
|-
 
|-
  
Line 994: Line 994:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Automobile Production]]
 
|-
 
|-
  
Line 1,002: Line 1,002:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Beer Distribution LP]]
 
|-
 
|-
  
Line 1,010: Line 1,010:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Big Mac Attack]]
 
|-
 
|-
  
Line 1,017: Line 1,017:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Example of capital budgeting for four possible projects, where the objective is to decide which projects to choose in order to maximize the total return.</div>
|[[]]
+
|[[Capital Investment]]
 
|-
 
|-
  
Line 1,025: Line 1,025:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Diagnosing an infeasible set of linear constraints.</div>
|[[]]
+
|[[Infeasible]]
 
|-
 
|-
  
Line 1,033: Line 1,033:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Linear program to determine which product variants to produce and how labor should be allocated among the various production steps based on the workers’ skill sets.</div>
|[[]]
+
|[[Labor production allocation]]
 
|-
 
|-
  
Line 1,041: Line 1,041:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Demonstration of a grouped-integer domain. Fill in a square with the digits 1 through n2 such that the rows and columns all sum to the same value.</div>
|[[]]
+
|[[Magic Square]]
 
|-
 
|-
  
Line 1,050: Line 1,050:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[NLP with Jacobian]]
 
|-
 
|-
  
Line 1,058: Line 1,058:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Optimal can dimensions]]
 
|-
 
|-
  
Line 1,066: Line 1,066:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Optimal Production Allocation]]
 
|-
 
|-
  
Line 1,073: Line 1,073:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Allocate planes to origin/destination legs to maximize gross margin.</div>
|[[]]
+
|[[Plane allocation LP]]
 
|-
 
|-
  
Line 1,081: Line 1,081:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">1-D example illustrating local the problem of local optima.</div>
|[[]]
+
|[[Polynomial NLP]]
 
|-
 
|-
  
Line 1,090: Line 1,090:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Problems with Local Optima]]
 
|-
 
|-
  
Line 1,098: Line 1,098:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Production Planning LP]]
 
|-
 
|-
  
Line 1,105: Line 1,105:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Example of a quadratically constrained optimization problem with a quadratic objective function.</div>
|[[]]
+
|[[Quadratic Constraints]]
 
|-
 
|-
  
Line 1,113: Line 1,113:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Demonstrates how an nonlinear programming formulation can be used to solve a non- linear equation.</div>
|[[]]
+
|[[Solve using NLP]]
 
|-
 
|-
  
Line 1,121: Line 1,121:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Find a solution to a Sudoku puzzle.</div>
|[[]]
+
|[[Sudoku with Optimizer]]
 
|-
 
|-
  
Line 1,129: Line 1,129:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Find a minimal length tour through a set of cites.</div>
|[[]]
+
|[[Traveling salesman]]
 
|-
 
|-
  
Line 1,138: Line 1,138:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Two Mines Model]]
 
|-
 
|-
  
Line 1,146: Line 1,146:
 
|
 
|
 
|<div style="text-align: left;"></div>
 
|<div style="text-align: left;"></div>
|[[]]
+
|[[Vacation plan with PWL tax]]
 
|-
 
|-
  
Line 1,153: Line 1,153:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Projects cost assessments of damage resulting from large earthquakes over time. It demonstrates risk analysis with time-dependence and costs of events shifted over time.</div>
|[[]]
+
|[[Earthquake expense risk]]
 
|-
 
|-
  
Line 1,161: Line 1,161:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Compares the value of various policies for restraints on occupants of automobiles.</div>
|[[]]
+
|[[Seat belt safety]]
 
|-
 
|-
  
Line 1,169: Line 1,169:
 
|
 
|
 
|
 
|
|<div style="text-align: left;"></div>
+
|<div style="text-align: left;">Demonstrates risk/benefit analysis, in this case regarding the benefits of reducing the emissions of fictitious air pollutant TXC.</div>
|[[]]
+
|[[Txc]]
 
|-
 
|-
  

Revision as of 16:13, 18 January 2023


This page lists example models and libraries. You can download them from here or (in some cases) link to a page with more details. Feel free to include and upload your own models and libraries.

Model/Library Download Domain Methods Description For more
Model Marginal abatement home heating.ana carbon price, energy efficiency, climate policy graph methods, optimal allocation, budget constraint
Shows how to set up a Marginal Abatement graph in Analytica.
Marginal Abatement Graph
Model Solar Panel Analysis.ana renewable energy, photovoltaics, tax credits net present value, internal rate of return, agile modeling
Explores whether it would it be cost effective to install solar panels on the roof of a house in San Jose, California.
Solar Panel Analysis
Model Items within budget.ana
Given a set of items, with a priority and a cost for each, selects out the highest priority items that fit within the fixed budget.
Items within Budget function
Model Grant exclusion.ana business analysis
Tests a hypothesis about the distribution of an attribute of the marginal rejectee of a grant program, given the relevance of that attribute to award of the grant.
Grant Exclusion Model
Model Project Priorities 5 0.ana business models cost analysis, net present value (NPV), uncertainty analysis
Evaluates a set of R&D projects (including uncertain R&D costs/revenues), uses multiattribute analysis to compare projects & generates the best portfolio given a R&D budget.
Project Planner
Model Steel and aluminum tariff model.ana
Estimate of the net impact of the 2018 import tariffs on steel and aluminum on the US trade deficit.
Steel and Aluminum import tariff impact on US trade deficit
Model Tax bracket interpolation 2021.ana
Computes amount of tax due from taxable income for a 2017 US Federal tax return.
Tax bracket interpolation
Model Feasible Sampler.ana feasibility
Implements a button that will sample a collection of chance variables, then reset the sample size and keep only those sample points that are "feasible".
Model Cross-validation example.ana cross-validation, overfitting, non-linear kernel functions
Fits a non-linear kernel function to the residual error, and uses cross-validation to determine how many kernel functions should be used.
Cross-Validation / Fitting Kernel Functions to Data
Model Bootstrapping.ana bootstrapping, sampling error, re-sampling
Bootstrapping; estimates sampling error by resampling the original data.
Statistical Bootstrapping
Model Kernel Density Estimation.ana kernel density estimation, kernel density smoothing
Demonstrates a very simple fixed-width kernel density estimator to estimate a "smooth" probability density.
Smooth PDF plots using Kernel Density Estimation
Model Output and input columns.ana data analysis
Presents an input table to a user, where one column is populated with computed output data, the other column with checkboxes for the user to select.
Output and Input Columns in Same Table
Model Platform2018b.ana offshore platforms, oil and gas, stakeholders, rigs to reefs, decision support decision analysis, multi-attribute, sensitivity analysis
Determined how to decommission California's 27 offshore oil platforms.
From Controversy to Consensus: California's offshore oil platforms
Model Comparing retirement account types.ana or Free 101 Compatible Version 401(k), IRA, retirement account, decision analysis, uncertainty MultiTables, sensitivity analysis
Explores tradeoffs between different retirement account types.
Retirement plan type comparison
Model Plane catching with UI 2020.ANA decision theory, decision analysis, uncertainty, Monte Carlo simulation, value of information, EVPI, EVIU
Determines when you should leave home to catch an early morning plane departure.
Plane Catching Decision with Expected Value of Including Uncertainty
Model Marginal Analysis for Control of SO2 Emissions.ana environmental engineering cost-benefit analysis, marginal analysis
Marginal analysis a.k.a. benefit/cost analysis to determine the policy alternative that leads us to the most economically efficient level of cleanup of acid rain from coal-burning electric-generating plants.
Marginal Analysis for Control of SO2 emissions
Model Donor-Presenter Dashboard.ana dynamic models, Markov processes
Implements a continuous-time Markov chain in Analytica's discrete-time dynamic simulation environment. It supports immigration to, and emigration from, every node.
Donor/Presenter Dashboard
Model Photosynthesis Regulation.ana - main regulation pathways
Photosystem.ana - rough sketch of genetic regulation
photosynthesis dynamic models
A model of how photosynthesis is regulated inside a cyanobacteria. Simulates the concentration levels of key transport molecules along the chain.
Regulation of Photosynthesis
Model Time-series-reindexing.ana dynamic models, forecasting, time-series re-indexing
Examples of time-series re-indexing.
Time-series re-indexing
Model Post Compression Model
Calculator for computing the maximum load that can be handled by a Douglas Fir - Larch post of a given size, grade, and composition in a construction setting.
Timber Post Compression Load Capacity
Model Compression Post Load Capacity.ana compression analysis
Computes the load that a Douglas-Fir Larch post can support in compression. Works for different timber types and grades and post sizes.
Compression Post Load Calculator
Model Daylighting analyzer.ana engineering cost-benefits analysis
How to analyze lifecycle costs and savings from daylighting options in building design.
Daylighting Options in Building Design
Model California Power Plants.ana power plants edit table, choice menu, pulldown menu, checkbox
Example showing how to use Choice menus and Checkbox inside an Edit table.
California Power Plants
Model Requires Analytica Optimizer
Electrical Transmission.ana
electrical engineering, power generation and transmission
Electrical network model that minimizes total cost of generation and transmission.
Electrical Generation and Transmission
Model Time of use pricing.ana & MECOLS0620.xlsx
(both files needed)
reading from spreadsheets, time-of-use pricing, electricity pricing
Time-of-use pricing is a rate tariff model used by utility companies that changes more during times when demand tends to exceed supply.
Time of Use pricing
Model Color map.ana computed cell formatting
A model which highlights Cell Formatting and Computed Cell Formats.
Color Map
Model World cup.ana
Demonstrates the Poisson distribution to determine why France beat Croatia in 2018.
2018 World Cup Soccer final
Model resnet18.zip residual network, deep residual learning, image recognition
Show it an image, and it tries to recognize what it is an image of, classifying it among 1000 possible categories. It uses an 18-layer residual network.
Image recognition
Model Month to quarter.ana aggregation, level of detail, days, weeks, months, quarters, years
Shows how to transform an array from a finer-grain index (e.g., Month) onto a coarser index (e.g., Quarter). We generally refer to this as aggregation.
Transforming Dimensions by transform matrix, month to quarter
Model Convolution.ana signal analysis, systems analysis
Contains several examples of convolved functions.
Convolution
Model Dependency Tracker.ana dependency analysis
This module tracks dependencies through your model, updating the visual appearance of nodes so that you can quickly visualize the paths by which one variable influences another.
Dependency Tracker Module
Model French-English.ana multi-lingual models
Maintains a single influence diagram with Title and Description attributes in both English and French.
Multi-lingual Influence Diagram
Model Parsing XML example.ana data extraction, xml, DOM parsing
Demonstrates two methods for extracting data: Using a full XML DOM parser, or using regular expressions.
Extracting Data from an XML file
Model Vector Math.ana geospatial analysis, GIS, vector analysis
Functions used for computing geospatial coordinates and distances.
Vector Math
Model Total Allowable w Optimizer.ana or
Total Allowable w StepInterp.ana for those without Optimizer
population analysis, dynamic models, optimization analysis
Determines how many fish or animals can be caught (landed) annually so that the probability of the population declining X% in Y years (decline threshold) is less than Z% (risk tolerance).
Total Allowable Harvest
Model Cereal Formulation1.ana product formulation, cereal formulation
Cereal formulation/discrete mixed integer model that chooses product formulations to minimize total ingredient costs.
Linearizing a discrete NSP
Model Neural Network.ana feed-forward neural networks, non-linear regression optimization analysis
Models set up to train a 2-layer feedforward sigmoid network to "learn" the concept represented by the data set(s), and then test how well it does across examples not appearing in the training set.
Neural Network
Model Earthquake expenses.ana risk analysis, cost analysis
An example of risk analysis with time-dependence and costs shifted over time.
Earthquake Expenses
Model Best used with Analytica Optimizer
Loan policy selection.ana
creditworthiness, credit rating, default risk risk analysis
Helps a lender decide optimal credit rating threshold to require and what interest rate (above prime) to charge.
Loan Policy Selection
Model Hubbard_and_Seiersen_cyberrisk.ana cybersecurity risk loss exceedance curve, simulation
Simulates loss exceedance curves for a set of cybersecurity events, the likelihood and probabilistic monetary impact of which have been characterized by system experts.
Inherent and Residual Risk Simulation
Model Media:Red_State_Blue_State_plot.ana map, states graphing
Example containing the shape outlines for each of the 50 US states, along with a graph that uses color to depict something that varies by state.
Red or blue state
Model COVID Model 2020--03-25.ana covid, covid-19, coronavirus, corona, epidemic
A systems dynamics style SICR model of the COVID-19 outbreak within the state of Colorado.
COVID-19 State Simulator, a Systems Dynamics approach
Model Corona Markov.ana covid, covid-19, coronavirus, corona, epidemic, sensitivity analyses
Explores the progression of the COVID-19 coronavirus epidemic in the US, and to explore the effects of different levels of social isolation.
How social isolation impacts COVID-19 spread in the US - A Markov model approach
Model Modelo Epidemiológoco para el Covid-19 con cuarentena.ana covid, covid-19, coronavirus, corona, epidemic
Un modelo en cadena de Markov del impacto previsto de la enfermedad coronavirus COVID-19 en el Perú, y del impacto del aislamiento social.
Epidemiological model of COVID-19 for Perú, en español
Model COVID-19 Triangle Suppression.ana covid, covid-19, coronavirus, corona, epidemic
Models progression of the COVID-19 pandemic in the US, understanding the amount of time that is required for lock down measures when a suppression strategy is adopted.
A Triangle Suppression model of COVID-19
Model Simple COVID-19.ana covid, covid-19, coronavirus, corona, epidemic
Explores possible COVID-19 Coronavirus scenarios from the beginning of March, 2020 through the end of 2020 in the US.
COVID-19 Coronavirus SICR progression for 2020
Model US COVID-19 Data.ana covid, covid-19, coronavirus, corona, epidemic, death, infection
Reads in COVID-19 data from the New York Times and transforms it into a form that is convenient to work with in Analytica.
COVID-19 Case and Death data for US states and counties
Model Voluntary vs mandatory testing.ana covid, covid-19, coronavirus, corona, epidemic
Computes the rate of infection in scenarios when COVID-19 testing is required/optional,based on prevalence rates, test accuracies and voluntary testing rates.
Mandatory vs Voluntary testing policies
Library Included with software
Bond Model
Library Included with software
Breakeven Analysis
Library Included with software
Expected R&D Project Value
Library Included with software
Financial Statement Templates
Library Included with software
Market Model
Library Included with software
Plan_Schedule_ Control
Library Included with software
Project Portfolio Planner
Library Included with software
Sales Effectiveness
Library Included with software
Subscriber Pricing
Library Included with software
Waterfall chart
Library Included with software
Bootstrapping
Library Included with software
Kmeans Clustering
Library Included with software
Logistic regression prior selection
Library Included with software
Moving Average Example
Library Included with software
Multidimensional Scaling
Library Included with software
Principle Components
Library Included with software
Regression Examples
Library Included with software
Two Branch Party Tree
Library Included with software
Beta Updating
Library Included with software
Biotech R&D Portfolio
Library Included with software
Diversification Illustration
Library Included with software
Expected Value of Sampling Information (EVSI)
Library Included with software
Gibbs Sampling in Bayesian Network
Library Included with software
LEV R&D Strategy
Library Included with software
Marginal Analysis for Control of SO2 Emissions
Library Included with software
Multi-attribute Utility Analysis
Library Included with software
Newton-Raphson Method
Library Included with software
Nonsymmetric Tree
Library Included with software
Party With Forecast
Library Included with software
Plane catching decision with EVIU
Library Included with software
Probability of Gaussian Region (Importance Sampling)
Library Included with software
Supply and Demand
Library Included with software
Tornado Diagrams
Library Included with software
Upgrade Decision
Library Included with software
Disease establishment
Library Included with software
Leveling
Library Included with software
Markov Chain
Library Included with software
Mass-Spring-Damper
Library Included with software
Mean-reversion trading
Library Included with software
Minimal edit distance
Library Included with software
Optimal Path Dynamic Programming
Library Included with software
Parking Space Selection
Library Included with software
Projectile Motion
Library Included with software
Tunnel through earth
Library Included with software
Unequal time steps
Library Included with software
Curve fits noisy time-sequence data using an adaptive filter.
Adaptive Filter
Library Included with software
Calculates the expected gain of an antenna looking at two different satellites.
Antenna Gain
Library Included with software
Computes the load that a Douglas-Fir Large compression post can support.
Compression Post Load Capacity
Library Included with software
Demonstration showing how to analyze life cycle costs and savings from daylighting options in building design.
Daylight Analyzer
Library Included with software
Failure Analysis
Library Included with software
Ideal Gas Law
Library Included with software
Power dispatch
Library Included with software
Regular polygon calculator
Library Included with software
Find Words Game
Library Included with software
Fractals everywhere
Library Included with software
Probability assessment
Library Included with software
Abstracted Subset
Library Included with software
Assignment from Button
Library Included with software
Calculates the auto-correlation coefficients of noisy time sequence data.
Autocorrelation
Library Included with software
Choice and Determtables
Library Included with software
Correlated Distributions
Library Included with software
Correlated Normals
Library Included with software
DBWrite Example
Library Included with software
Discrete Sampling
Library Included with software
Demonstrates how to extract a diagonal from a matrix.
Extracting Diagonal
Library Included with software
Lookup Reindexing
Library Included with software
Map images from internet
Library Included with software
Sample Size Input Node
Library Included with software
Sorting People by Height
Library Included with software
Creates a subset array out of a larger array based on a decision criterion.
Subset of Array
Library Included with software
Swaps a computed or one-dimensional table value with its index, thereby making the computed value an index.
Swapping y and x-index
Library Included with software
Use of MDTable
Library Included with software
Airline NLP
Library Included with software
Asset allocation
Library Included with software
Automobile Production
Library Included with software
Beer Distribution LP
Library Included with software
Big Mac Attack
Library Included with software
Example of capital budgeting for four possible projects, where the objective is to decide which projects to choose in order to maximize the total return.
Capital Investment
Library Included with software
Diagnosing an infeasible set of linear constraints.
Infeasible
Library Included with software
Linear program to determine which product variants to produce and how labor should be allocated among the various production steps based on the workers’ skill sets.
Labor production allocation
Library Included with software
Demonstration of a grouped-integer domain. Fill in a square with the digits 1 through n2 such that the rows and columns all sum to the same value.
Magic Square
Library Included with software
NLP with Jacobian
Library Included with software
Optimal can dimensions
Library Included with software
Optimal Production Allocation
Library Included with software
Allocate planes to origin/destination legs to maximize gross margin.
Plane allocation LP
Library Included with software
1-D example illustrating local the problem of local optima.
Polynomial NLP
Library Included with software
Problems with Local Optima
Library Included with software
Production Planning LP
Library Included with software
Example of a quadratically constrained optimization problem with a quadratic objective function.
Quadratic Constraints
Library Included with software
Demonstrates how an nonlinear programming formulation can be used to solve a non- linear equation.
Solve using NLP
Library Included with software
Find a solution to a Sudoku puzzle.
Sudoku with Optimizer
Library Included with software
Find a minimal length tour through a set of cites.
Traveling salesman
Library Included with software
Two Mines Model
Library Included with software
Vacation plan with PWL tax
Library Included with software
Projects cost assessments of damage resulting from large earthquakes over time. It demonstrates risk analysis with time-dependence and costs of events shifted over time.
Earthquake expense risk
Library Included with software
Compares the value of various policies for restraints on occupants of automobiles.
Seat belt safety
Library Included with software
Demonstrates risk/benefit analysis, in this case regarding the benefits of reducing the emissions of fictitious air pollutant TXC.
Txc
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Library Included with software
[[]]
Comments


You are not allowed to post comments.