AbstractAn extended growth curve model is considered which, among other things, is useful when linear restrictions exist on the mean in the ordinary growth curve model. The maximum likelihood estimators consist of complicated stochastic expressions. It is shown how, by the aid of fairly elementary calculations, the dispersion matrix for the estimator of the mean and the expectation of the estimated dispersion matrix are obtained. Results for Wishart, inverted Wishart, and inverse beta variables are utilized. Additionally, some asymptotic results are presented
The extended growth curve model is discussed in this paper. There are two versions of the model stud...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
summary:The Extended Growth Curve Model (ECGM) is a multivariate linear model connecting different m...
AbstractAn extended growth curve model is considered which, among other things, is useful when linea...
AbstractA unified approach of treating multivariate linear normal models is presented. The results o...
AbstractThe growth curve model (Potthoff and Roy, 1964) and an extension (von Rosen, 1989) are consi...
AbstractStandard and extended growth curve model (multivariate linear model) with practically import...
A new approach of estimating parameters in multivariate models is introduced. A fitting function wil...
AbstractA new approach of estimating parameters in multivariate models is introduced. A fitting func...
AbstractEstimation of parameters in the classical Growth Curve model, when the covariance matrix has...
In this paper, we consider the general growth curve model with multivariate random effects covarianc...
Estimation of parameters in the classical Growth Curve model when the covariance matrix has some spe...
The problem of estimating the parameters of several growth curves has been considered for the case w...
Growth-curve models are generalized multivariate analysis-of-variance models. The basic idea of the ...
Growth-curve models are generalized multivariate analysis-of-variance models. These models are espec...
The extended growth curve model is discussed in this paper. There are two versions of the model stud...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
summary:The Extended Growth Curve Model (ECGM) is a multivariate linear model connecting different m...
AbstractAn extended growth curve model is considered which, among other things, is useful when linea...
AbstractA unified approach of treating multivariate linear normal models is presented. The results o...
AbstractThe growth curve model (Potthoff and Roy, 1964) and an extension (von Rosen, 1989) are consi...
AbstractStandard and extended growth curve model (multivariate linear model) with practically import...
A new approach of estimating parameters in multivariate models is introduced. A fitting function wil...
AbstractA new approach of estimating parameters in multivariate models is introduced. A fitting func...
AbstractEstimation of parameters in the classical Growth Curve model, when the covariance matrix has...
In this paper, we consider the general growth curve model with multivariate random effects covarianc...
Estimation of parameters in the classical Growth Curve model when the covariance matrix has some spe...
The problem of estimating the parameters of several growth curves has been considered for the case w...
Growth-curve models are generalized multivariate analysis-of-variance models. The basic idea of the ...
Growth-curve models are generalized multivariate analysis-of-variance models. These models are espec...
The extended growth curve model is discussed in this paper. There are two versions of the model stud...
The field of statistics is becoming increasingly more important as the amount of data in the world g...
summary:The Extended Growth Curve Model (ECGM) is a multivariate linear model connecting different m...