We consider the problem of estimating the period of an unknown periodic function observed in additive Gaussian noise sampled at irregularly spaced time instants in a semiparametric setting. To solve this problem, we propose a novel estimator based on the cumulated Lomb-Scargle periodogram. We prove that this estimator is consistent, asymptotically Gaussian and we provide an explicit expression ...

OLS estimation of an impulse-indicator coefficient is inconsistent, but its variance can be consistently estimated. Although the ratio of the inconsistent estimator to its standard error has a tdistribution, that test is inconsistent: one solution is to form an index of indicators. We provide Monte Carlo evidence that including a plethora of indicators need not distort model selection, permitti...

A panel of ex-ante forecasts of a single time series is modeled as a dynamic factor model, where the conditional expectation is the single unobserved factor. When applied to out-of-sample forecasting, this leads to combination forecasts that are based on methods other than OLS. These methods perform well in a Monte Carlo experiment. These methods are evaluated empirically in a panel of simulate...

Several algorithms for indicator saturation are compared and found to have low power when there are multiple breaks. A new algorithm is introduced, based on repeated application of an automatic model selection procedure (Autometrics, see Doornik, 2009) which is based on the general-to-specific approach. The new algorithm can also be applied in the general case of more variables than observation...

We discuss the pricing of cancellable swaps using the displaced diffusion LIBOR market model using a multi-core graphics card. We demonstrate that over one hundred times speed up can be achieved in a realistic case.

Abstract In this paper, we analytically investigate three efficient estimators for cointegrating regression models: Phillips and Hansen’s (1990) fully modified OLS estimator, Park’s (1992) canonical cointegrating regression estimator, and Saikkonen’s (1991) dynamic OLS estimator. We consider the case where the regression errors are moderately serially correlated and the AR coefficient in the re...

Least-squares optimized polynomials are discussed which are needed in the twostep multi-bosonic algorithm for Monte Carlo simulations of quantum field theories with fermions. A recurrence scheme for the calculation of necessary coefficients in the recursion and for the evaluation of these polynomials is introduced.

The widely-used LMS algorithm for coefficient updates in adaptive (feedforward/decision-feedback) equalizers is found to be suboptimal for ASE-dominant systems but various coefficient-dithering approaches suffer from slow adaptation rate without guarantee of convergence. In view of the non-Gaussian nature of optical noise after the square-law optoelectronic conversion, we propose to apply the h...

Least squares regression based on probability plots, also called rank regression, can be used to estimate the parameters of some distributions. Regression is performed between a function of the empirical distribution function and the order statistic as the independent variable. Using large sample properties of the empirical distribution function and order statistics, weights to stabilize the va...

In this paper, localization based on Received Signal Strength (RSS) is investigated assuming a path loss log normal shadowing model. RSS-based estimation schemes of ranges are investigated; three different schemes are studied: Mean, median and mode. Estimation of position is performed using weighted least square approximation. We show that the positioning accuracy depends on the used estimator ...