Description Usage Arguments Details Value References Examples
Modeling Judgments of Frequency with MINERVA 2
1 |
x |
input handled by MINERVA 2. Values -1, 0 and 1 are allowed. -1 represents the absence of a feature, 0 the irrelevance of a feature and 1 the presence of a feature. |
y |
another input handled by MINERVA 2. At least two inputs are needed for the simulation. |
... |
other inputs for modeling. |
sqc |
sequence of the different objects. Each input gets
an ascending number. |
L |
learning parameter. This is the proportion of a
correctly stored vector. |
dec |
decay is not part of the original version of MINERVA 2.
This is just implemented for a better comparison with the other
models of JoF. In |
Calculations of MINERVA 2 contain four steps.
Si = (sum(Pj)*Tj) / Ni
Ai = Si^3
I = sum(Ai)
relative JoF = Ij / Sum(Ij)
MINERVA2 returns the relative judgment of frequency
Dougherty, M. R., Gettys, C. F., & Ogden, E. E. (1999). MINERVA-DM: A memory processes model for judgments of likelihood. Psychological Review, 106(1), 180.
Hintzman, D. L. (1984). MINERVA 2: A simulation model of human memory. Behavior Research Methods, Instruments, and Computers, 16, 96–101.
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