multiCycle: multiCycle

In dlandy/WarpedBayes: Implements Design Pattern Discussed in Landy, Crawford, & Corbin

Description

Divides a mapping, of any sort (bounded, semi-bounded, or unbounded) into a finite number of distinct regions, by creating 'references' inside the space. Functionally, multiCycle simply divides a vector of stimuli into A list of vectors of values based on their proportional distances between two references. Usually, these are then fed into a psi function which creates a multiCycle space containing multiple infinite unbounded regions which are conceptually adjacent

Usage

multiCycle(stimuli, references = c(0))

Arguments

stimuli	a vector of stimuli, between -inf and inf, or a list of vectors of stimuli
references	A vector of values. This should include -Inf and Inf, but these are implicitly added if they are omitted

Details

For instance, a spatial region |—————-| might be divided by a line of vertical symmetry into two regions |——–||——–| And each be turned int an unbounded Prelec region <——–><——–> with a command like -10:10

Value

A vector containing warped stimuli, or a list of vectors

See Also

psiIdentity, multiCycleInverse

Examples

multiCycle(-99:100, c(-100, 0, 100))
(-99:100/100) %>% multiCycle(references= c(-1, 0, 1)) %>% 
    psiLogOdds() %>% vanillaBayes() %>% 
    psiLogOddsInverse() %>% multiCycleInverse(references=c(-1, 0, 1)) 
    # Implements Landy et al's model of one-dimensional spatial memory, with fixed boundaries
plot(-99:100, unlist(multiCycle(-99:100, c(-100, -50, 0, 50, 100))))
plot(-99:100/100, (-99:100/100) %>% multiCycle(references= c(-1, 0, 1)) %>% 
    psiLogOdds() %>% vanillaBayes(kappa=c(-.8, .8)) %>% 
    psiLogOddsInverse() %>%
     multiCycleInverse(references=c(-1, 0, 1))-(-99:100/100),
          ylab="bias", xlab="stimulus");abline(0,0)

dlandy/WarpedBayes documentation built on May 29, 2019, 2:49 p.m.