Occasionally, situations arise where mixtures of two binomials with one known success parameter are met. An example in educational testing is the mastery or random guessing model in which an examinee is supposed either to master the items or not to master them and to guess blindly. This paper gives moment estimators for such mixtures and presents results from a Monte Carlo investigation into their statistical properties. The results suggest excellent estimators that can safely be used in most instances. It also indicates how the properties of these estimators relate to those of moment estimators for the case in which both success parameters are unknown. Finally, it is pointed out that in situations in which errors in specifying the true val...
With recent advances in approximate inference, Bayesian methods have proven successful in larger dat...
Mixture modeling is a general technique for making any simple model more ex-pressive through weighte...
Latent class models for mastery testing differ from continuum models in that they do not postulate a...
Occasionally, situations arise where mixtures of two binomials with one known success parameter are ...
7 pages, 1 article*Some Remarks on the Use of Moment Estimators for the Parameters of a Mixture of T...
Mixture of binomial distributions are often considered as a flexible model for count data which can ...
In this note, we study the first four moments of the MUB random variable, that is a mixture of two d...
Blischke [1962. Moment estimators for the parameters of a mixture of two binomial distributions. Ann...
In mixture distributions, mixing parameter is an important parameter. In this paper we estimate this...
In this paper, we study the estimation and inference problems for parameters when the data set is ob...
A recent thread of research in ordinal data analysis involves a class of mixture models that designs...
We consider the problem of identifying the parameters of an unknown mixture of two ar-bitrary d-dime...
by Tse Siu-Keung.Thesis (M.Phil.)--Chinese University of Hong Kong.Bibliography: leaves 47-48
We consider the problem of identifying the parameters of an unknown mixture of two arbi-trary d-dime...
International audienceIn this paper the factorial moment method is used to obtain parameter estimate...
With recent advances in approximate inference, Bayesian methods have proven successful in larger dat...
Mixture modeling is a general technique for making any simple model more ex-pressive through weighte...
Latent class models for mastery testing differ from continuum models in that they do not postulate a...
Occasionally, situations arise where mixtures of two binomials with one known success parameter are ...
7 pages, 1 article*Some Remarks on the Use of Moment Estimators for the Parameters of a Mixture of T...
Mixture of binomial distributions are often considered as a flexible model for count data which can ...
In this note, we study the first four moments of the MUB random variable, that is a mixture of two d...
Blischke [1962. Moment estimators for the parameters of a mixture of two binomial distributions. Ann...
In mixture distributions, mixing parameter is an important parameter. In this paper we estimate this...
In this paper, we study the estimation and inference problems for parameters when the data set is ob...
A recent thread of research in ordinal data analysis involves a class of mixture models that designs...
We consider the problem of identifying the parameters of an unknown mixture of two ar-bitrary d-dime...
by Tse Siu-Keung.Thesis (M.Phil.)--Chinese University of Hong Kong.Bibliography: leaves 47-48
We consider the problem of identifying the parameters of an unknown mixture of two arbi-trary d-dime...
International audienceIn this paper the factorial moment method is used to obtain parameter estimate...
With recent advances in approximate inference, Bayesian methods have proven successful in larger dat...
Mixture modeling is a general technique for making any simple model more ex-pressive through weighte...
Latent class models for mastery testing differ from continuum models in that they do not postulate a...