In this paper we present a test statistic, which will be used to test for significant differences between generating processes of two time series that may be logically connected. The test statistic is based on the differences between estimated parameters of the autoregressive models which are...

In this paper two new estimators are offred (one each for the fixed random effects specifications), and small sample performance compared with that of all the existing estimators.

This study proposes a new approach to estimation of the time series properties of daily volatility in financial markets.

In this paper the EM algorithm, which has been used successfully with censored and incomplete data sets, is adapted to the problem of scrambled data. The performance of the method is assayed using an artificially constructed data set. The relevance of the results for a real world labour market...

We consider bandwidth selection for the kernel estimator of conditional density with one explanatory variable. Several bandwidth selection methods are derived ranging from fast rules-of-thumb which assume the underlying densities are known to relatively slow procedures which use the bootstrap....

A new simple formula is found to correct the underestimation of the standard deviation for total lead time demand when using simple exponential smoothing. This new formula allows one to see readily the significant size of the underestimation of the traditional formula and can easily be...

This paper considers the analysis of cointegrated time series using principal components methods. These methods have the advantage of neither requiring the normalisation imposed by the triangular eror correction model, nor the specification of a finite order vector autoregression.

This paper derives six different forms of message length functions for general linear regression model. In so doing, two different prior densities and the idea of parameter orthogonality are employed.

This study proposes a new approach to the estimation of daily volatility. This approach is different ( in the sense of using all available intraday price data) and unbiased ( in the sense of accounting for the high levels of autocorrelation found in intraday price data).