The inference about the population mean based on the standard t-test involves the assumption of normal population as well as independence of the observations. In this paper we examine the robustness of the inference in the presence of correlations among the observations. We consider the simplest...

In this paper Markov Chain Monte Carlo algorithms(MCMC) are developed to facilitate the Bayesian analysis on nested designs when the error structure can be expressed as an autoregressive process of order one. Simulated and real data are also presented to confirm the efficiency and high accuracy...

Consider the wavelet estimator of a nonparametric regression model with repeated measurements under martingale difference error’s structure for exhibiting dependence among the units, and to avoid as far as possible any assumptions among the observations within the same unit. We show the moment...

The intraclass correlation coefficient and the concordance correlation coefficient are two popular scaled indices for assessing the closeness between observers who make measurements for quantitative responses. These two indices are usually based on subject and observer effects only, and...

Discriminant analysis (DA) procedures based on parsimonious mean and/or covariance structures have recently been proposed for repeated measures data. However, these procedures rest on the assumption of a multivariate normal distribution. This study examines repeated measures DA (RMDA) procedures...

To enhance the efficiency of regression parameter estimation by modeling the correlation structure of correlated binary error terms in quantile regression with repeated measurements, we propose a Gaussian pseudolikelihood approach for estimating correlation parameters and selecting the most...

AMS classifications: 62G10, 62G20; 62J05.

By incorporating the Harvey accumulator into the large approximate dynamic factor framework of Doz et al. (2006), we are able to construct a coincident index of financial conditions from a large unbalanced panel of mixed frequency financial indicators. We relate our financial conditions index,...

This paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM...