Many children in primary grades show difficulties with reading fluency, hardly reading text or doing it effortfully and fruitlessly, making intervention programs for struggling readers a priority for researchers and schools. This paper analyzes the results of a reading intervention program for...

Many children in primary grades show difficulties with reading fluency, hardly reading text or doing it effortfully and fruitlessly, making intervention programs for struggling readers a priority for researchers and schools. This paper analyzes the results of a reading intervention program for...

In statistical data analysis it is often important to compare, classify, and cluster different time series. For these purposes various methods have been proposed in the literature, but they usually assume time series with the same sample size. In this paper, we propose a spectral domain method...

This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are...

Previous studies have investigated the comovements of international equity markets by using correlation, cointegration, common factor analysis, and other approaches. In this paper, we investigate the stochastic structure of major euro and non-euro area stock market series from 1994 to 2006, by...

This paper proposes spectral and asymmetric-volatility based methods for cluster analysis of stock returns. Using the information about both the periodogram of the squared returns and the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are...

The comparison and classification of time series is an important issue in practical time series analysis. For these purposes, various methods have been proposed in the literature, but all have shortcomings, especially when the observed time series have different sample sizes. In this paper, we...

Previous studies have investigated the comovements of international equity returns by using mean correlations, cointegration, common factor analysis, and other approaches. This paper investigates the evolution of the affinity among major euro and non-euro area stock markets in the period...

In this paper, we introduce a volatility-based method for clustering analysis of financial time series. Using the generalized autoregressive conditional heteroskedasticity (GARCH) models we estimate the distances between the stock return volatilities. The proposed method uses the volatility...

We propose a periodogram-based metric for classification and clustering of time series with different sample sizes. For such cases, we know that the Euclidean distance between the periodogram ordinates cannot be used. One possible way to deal with this problem is to interpolate lineary one of...