In the 1980’s author proved lower bounds for mean value of modulus error term prime number theorem and other important theoretic functions whose oscillation is in connection with zeros Riemann zeta function. present work a general shown simple way which gives bound mentioned as function hypothetical pole Mellin transform The conditions are amply satisfied such results recover earlier ones (even...

We present a method for the separation of superimposed, independent, autocorrelated components from noisy multichannel measurement. The presented method simultaneously reconstructs and separates the components, taking all channels into account, and thereby increases the effective signal-to-noise ratio considerably, allowing separations even in the high-noise regime. Characteristics of the measu...

This paper analyses persistence in US interest rates. It focuses on the Federal Funds effective rate, whose degree of persistence is modelled using fractional integration, monthly from July 1954 through March 2008. The full-sample estimates of the fractional differencing parameter appear to be very sensitive to the choice of the I(0) error term; specifically, the order of integration is strictl...

This paper proposes a new GMM estimator for spatial regression models with moving average errors. Monte Carlo results are given indicating that the GMM estimates are close to expectation and robust to non-normality, and the Bootstrap method is suggested as a way of testing the significance of the moving average parameter. The estimator is applied in a model of English real estate prices, in whi...

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This dissertation studies the least squares estimator of a trend parameter in a simple linear regression model with multiple changepoints when the changepoint times are known. The error component in the model is allowed to be autocorrelated. The least squares estimator of the trend and the variance of the trend estimator are derived. Consistency and asymptotic normality of the trend estimator a...

SUMMARY In this paper we consiaer the problem wnere repeated measurements are taKen on eacn experimental unit of a randomized experimental design. If the design is a randomized complete block then traditionally a split-bloCK analysis is used. Here we consider an extension of tne traaitional sol it-bloCK analysis where \~e allow for several orthogonal autocorrelated error components deoending on...

Penalized regression methods have recently gained enormous attention in statistics and the field of machine learning due to their ability of reducing the prediction error and identifying important variables at the same time. Numerous studies have been conducted for penalized regression, but most of them are limited to the case when the data are independently observed. In this paper, we study a ...