OPIM 5504 Adaptive Business Intelligence


Study Guide for Exam #2
On 12-02-2020

Concepts:
 Markov chains: recursive formulas, one-step transition matrix, n-step transition matrix, state
transition network, random walk, steady-state probabilities, long-run expected cost per time unit,
Markov chain simulation for short-runs, confidence intervals, Markov chain estimation based on
historical data.
 Linear Optimization: decision variables, objective function, constraints, feasible and infeasible
problems, linear expressions, sensitivity analysis, scenario simulation, confidence intervals.
 Monte Carlo optimization: nonlinear optimization, random decision variable generation, naïve
MC optimization.
 Adaptive methods: predicted modeling, prediction errors, MAE and MSE, MSE updating,
prediction error tolerance.
 Review homework assignments and class examples.

Shiny Topics:
 Input functions: actionButton, checkboxInput, numericInput, sliderInput, textInput,
checkboxGroupInput, radioButtons, selectInput, dateInput.
 Output functions: plotOutput, textOutput, verbatimTextOutput, tableOutput, dataTableOutput,
imageOutput.
 Render functions: renderPlot, renderText, renderTable, renderDataTable, renderImage.
 Special functions: reactive, HTML tags, hr, observeEvent, reactiveTimer.
 Layout details: titlePanel, sidebarLayout, sidebarPanel, mainPanel.

R Topics:
 External Excel files: read.xlsx, write.xlsx.
 Special functions: paste, paste0, lm, glm, round, <<- assignment.
 Graphs: curve, plot, hist, barplot.
 Simulation functions: r functions (rnormal, rbinom, rexp, rpois, rbeta, etc.), sample, replicate,
quantile.
 Optimization functions: min, max, which.min, which.max, lp.
 Markov chain functions: steadyStates, conditionalDistribution.
 Control Statements: for-loops, repeat, if, ifelse, switch, break.
 Objects: data frames, lists, numeric arrays, character arrays, markovchain, lp.
 Packages: markovchain, lpSolve, openxlsx, shiny.


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