Description Usage Arguments Value See Also Examples
A simple package that assembles the symmetric model used by Landy, Crawford, and Corbin, 2017 to analyze spatial estimations from memory in one dimension
1 2 3 4 5 6 7 8 9 | bayesianSpatialMemoryLandyCrawfordCorbin2017(stimuli,
kappa = psiLogOdds(multiCycle(kappaObjective, references =
c(leftBoundaryObjective, rightBoundaryObjective))), kappaObjective = 0.5,
tauStimuli = 1, tauCategory = 1, leftBoundaryObjective = minValue -
smallValue, rightBoundaryObjective = maxValue + smallValue,
rightBoundaryExpansion = NULL, leftBoundaryExpansion = NULL,
minValue = min(c(stimuli), na.rm = T), maxValue = max(c(stimuli), na.rm =
T), smallValue = 10^-10, responses = NULL, center = 0,
mode = "prediction", responseGrid = NULL)
|
stimuli |
a vector of stimuli, between -inf and inf |
kappa |
The location of the categories (presumed symmetric on both sides around the midline of the screen) |
kappaObjective |
The location of the categories measured in objective units |
tauStimuli |
The precision of the stimulus traces: should be a single number |
tauCategory |
The precision of the category distribution: should be a single number |
responses |
an optional vector of responses. If responses are given, the return value is the logLikelihood of the responses given the parameters |
center |
The posited (or fitted) psychological center of the screen (in public units: should be near the true center) |
responseGrid |
an optional vector of response structured Responses |
boundary |
The subject-specific location of the boundaries: may bear any relation to true stimuli, except that it should not leave real data outside the boundaries |
leftBoundary |
The location of the posited (or fitted) psychological left-hand boundary of the screen. Defaults to -1 * 'boundary' |
rightBoundary |
The location of the posited (or fitted) psychological right-hand boundary of the screen. Defaults to 'boundary' |
A vector the transformed stimuli, or the logLikelihood of them.
psiIdentity, multiCycleInverse
1 2 3 | bayesianSpatialMemoryLandyCrawfordCorbin2017(-99:100/100)
bayesianSpatialMemoryLandyCrawfordCorbin2017(-99:100/100, kappa=1, tauStimuli=2)
bayesianSpatialMemoryLandyCrawfordCorbin2017(1:100, kappa=1, tauStimuli=2, responses=2*(1:100)^.9)
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