Description Usage Arguments Details Value References See Also Examples
Fits a Quadrilateral Dissimilarity Model to same-different data.
1 2 3 4 5 6 | qdm(psi, start, respfun = c("logistic", "guessing", "gumbel", "gompertz",
"weibull", "cauchy", "shepardA", "shepardAneg", "shepardB",
"shepardBneg", "shepardD", "shepardDneg", "shepardE", "shepardEneg",
"shepardF", "shepardFneg"), bias = 0,
estimfun = c("minchi2", "ols", "wls"), optimizer = c("optim", "nlm"),
optimargs = list())
|
psi |
data object created with |
start |
starting values for parameter estimation. |
respfun |
function that describes relationship between discrimination probabilities and similarity measure, see Details. |
bias |
takes perceptual bias into account. Default is 0. |
estimfun |
method to estimate parameters, see Details. |
optimizer |
which optimizer should be used: |
optimargs |
takes additional arguments passed to |
More details about the Quadrilateral Dissimilarity Model can be found in Dzhafarov and Colonius (2006).
Via respfun
, different functions can be selected to describe the
relationship between discrimination probabilities and dissimilarity
measure. Implemented are the logistic function (logistic
),
the logistic function with guessing parameter (guessing
), several
other functions commonly used as psychometric functions (gumbel
,
gompertz
, weibull
, cauchy
), and five functions
suggested by Shepard (1987) (shepardA
, shepardB
,
shepardD
, shepardE
, shepardF
) and their negatives
(shepardAneg
, shepardBneg
, shepardDneg
shepardEneg
, shepardFneg
). Default is the logistic
function. Note that for some of these functions the results critically
depend on the choice of the starting values.
Parameters can be estimated by using different minimizing functions
available via the estimfun
argument: ordinary least squares
(ols
), weighted least squares (wls
), and minimization of
Pearson's X^2 (minchi2
). Default is the minimization of
X^2.
An object of class qdm
that consists of the following components:
optimout |
output of optimizer ( |
coefficients |
estimated parameters. |
psi |
|
respfun |
function used to describe relationship between discrimination probabilities and similarity measure. |
bias |
perceptual bias used in the model. |
Dzhafarov, E. N., & Colonius, H. (2006). Regular Minimality: A fundamental law of discrimination. In H. Colonius & E. N. Dzhafarov (Eds.), Measurement and representation of sensations (pp. 1–46). Hillsdale, NJ: Lawrence Erlbaum Associates.
Shepard, R. N. (1987). Towards a universal law of generalization for psychological science. Science, 237, 1317–1323.
psi
, predict.qdm
, persp.qdm
,
nlm
, optim
.
1 2 3 4 5 6 7 8 9 10 11 12 |
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