polycor_mle {robcat} | R Documentation |
Maximum likelihood estimation of polychoric correlation coefficient
Description
Implements the maximum likelihood estimator of Olsson (1979, Psychometrika, doi:10.1007/BF02296207) for the polychoric correlation model.
Usage
polycor_mle(
x,
y = NULL,
variance = TRUE,
constrained = TRUE,
twostep = FALSE,
method = ifelse(constrained, "Nelder-Mead", "L-BFGS-B"),
maxcor = 0.999,
tol_thresholds = 0.01,
init = initialize_param(x, y)
)
Arguments
x |
Vector of integer-valued responses to first item, or contingency table (a |
y |
Vector of integer-valued responses to second item; only required if |
variance |
Shall an estimated asymptotic covariance matrix be returned? Default is |
constrained |
shall strict monotonicity of thresholds be explicitly enforced by linear constraints? Only relevant if |
twostep |
Shall two-step estimation of Olsson (1979) <doi:10.1007/BF02296207> be performed? Default is |
method |
Numerical optimization method; default is Nelder-Mead. |
maxcor |
Maximum absolute correlation (to ensure numerical stability). Deafult is 0.999. |
tol_thresholds |
Minimum distance between consecutive thresholds (to enforce strict monotonicity); only relevant if |
init |
Initialization of numerical optimization. Default is neutral. If |
Value
An object of class "robpolycor"
. See polycor()
for details.
Examples
## example data
set.seed(123)
x <- sample(c(1,2,3), size = 100, replace = TRUE)
y <- sample(c(1,2,3), size = 100, replace = TRUE)
polycor(x,y) # robust
polycor_mle(x,y) # non-robust MLE