Man pages for avilesd/productConfig
Tools to analyze behavioral patterns from Product Configurators
| benefitToCostAttr | Converts benefit type attributes to cost type, within a list |
| decisionMatrix | Creates the decision matrix |
| differenceToIdeal | Calculates decision weights using the 'objective approach' |
| dualGainLossFunction | Calculates the gain-loss matrix from a decision matrix |
| dualLossAversionFun | Takes a gain-loss matrix and outputs a value matrix |
| dual.valueMatrix | Returns a Value Matrix using two reference points |
| dualValueMatrix | (Deprecated)Returns a Value Matrix using two reference points |
| dualValueMatrix.oneAttr | Returns a Value Matrix using two reference points (one... |
| entropy | Calculates decision weights using the entrophy method |
| gainFunction | Calculates the gain for one single value |
| gainLoss | Merges gain and loss matrices |
| gainMatrix | Gain matrix |
| getAllUserIds | Get all user IDs |
| get_attrs_ID | Get the amount of attributes and their IDs |
| getAttrValues | All unique values for any given attribute |
| getAttrWeights | Weights calculating function |
| getDefaultRefps | Get Default Reference Points for selected user |
| getRoundsById | Get the amount of rounds (clicks) for each user |
| getTableById | Extract the part of the provided dataset that corresponds to... |
| highestValue | Calculates weights relative to the highest sum relative to... |
| lossFunction | Calculates the loss for one single value |
| lossMatrix | Loss matrix |
| normalize | Normalize a vector |
| normalize.altMethod | Alternative method for normalizing matrices |
| normalize.highestValue | Auxiliary function for calculating weights |
| normalize.sum | Title |
| norm.gainLoss | Normalizes gain and loss matrices |
| overallDRP | Calcultes the overall prospect values using the DRP approach... |
| overallPV | Calcultes the overall prospect values using PT (prospect... |
| overall_pv_extend | Calculate Prospect Values |
| overallPV_interface | cost_ids, enter normal reference points, we will convert... |
| overallTRP | Calcultes the overall prospect values using the TRP approach... |
| prospect_value_matrix_extend | Calculate Value Matrix |
| pvalue_fun | Implements prospect theory's value function |
| pvMatrix | Calcultes the Value Matrix |
| referencePoints | Delivers the Reference Points |
| replaceNotNA | Auxiliary function used for testing. |
| smallerThanZero | Outputs a value matrix from a decision matrix |
| standardDeviation | Calculates decision weights using the standard deviation... |
| trpValueFunction | Transform a decision Matrix into a trp value matrix |
| trpValueFunction_extend | TTri Reference Point Value Function for one element |
| trp.valueMatrix | Returns a Value Matrix using three reference points |
| trpValueMatrix | (Deprecated)Returns a Value Matrix using three reference... |
| trpValueMatrix.oneAttr | Returns a Value Matrix using three reference points (one... |
| weight.differenceToIdeal | Calculates attribute weights using the 'objective approach' |
| weight.entropy | Calculates decision weights using the entropy method |
| weight.highAndStandard | Calculates weights using two weighted sub-functions |
| weight.highestValue | Calculates weights relative to the highest sum relative to... |
| weight.standard | Calculates decision weights using the standard deviation |
