Cross-spectral analysis is commonly used in climate research to identify joint variability between two variables and to assess the phase (lead/lag) between them. Here we present a Fortran 90 program (REDFIT-X) that is specially developed to perform cross-spectral analysis of unevenly spaced paleoclimate time series. The data properties of climate time series that are necessary to take into acco...

The affine combination of two adaptive filters that simultaneously adapt on the same inputs has been actively investigated. In these structures, the filter outputs are linearly combined to yield a performance that is better than that of either filter. Various decision rules can be used to determine the time-varying parameter for combining the filter outputs. A recently proposed scheme based on ...

Partial least squares linear discriminant function (PLSD) as well as ordinary linear discriminant function (LDF) are used in pattern recognition analysis of writer identification based on arc patterns extracted from the writings written with Hangul letters by 20 Koreans. Also a simulation study is performed using the Monte Carlo method to compare the performances of PLSD and LDF. PLSD showed re...

This paper investigates the connection between market valuation anda type of the merger (stock, cash) using real options setup. I solveexplicitly for the timing and terms of cash mergers in two deferent settingsto demonstrate that cash mergers generally occur at low marketvaluations, whereas stock mergers that may be observed at both low andhigh valuations; the result holds with some dierences ...

Aims. We investigate the nature of the massive star [OMN2000] LS1 and use these results to constrain the history of star formation within the host complex W51. Methods. We utilised a combination of near-IR spectroscopy and non-LTE model atmosphere analysis to derive the physical properties of [OMN2000] LS1, and a combination of theoretical evolutionary calculations and Monte Carlo simulations t...

This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The asymptotic uniform linearity of a suitable vector of rank statistics leads to the asymptotic normality of √ n-consistent R-estimates resulting from the minimization of the norm of this vector. By using a discretized √ n-consistent preliminary estimate, we construct a new class of one-step R-estim...

An algorithm for smoothing results of three-dimensional Monte Carlo ion implantation simulations and translating them from the grid used for the Monte Carlo simulation to an arbitrary unstructured three-dimensional grid is presented. This algorithm is important for joining various process simulation steps, where data has to be smoothed or translated from one grid to another. Our algorithm sweep...

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.

This paper analyzes a spurious regression involving AR(p) infinite-variance processes in the presence of structural breaks by least squares using asymptotic theory. It is found that when regressing two independent infinite-variance sequence with breaks in the level and slope of trend, no matter whether the breaks occur at different points or not, the t-ratios become divergent and spurious pheno...

background: the monte carlo method is the most accurate method for simulation of radiation therapy equipment. the linear accelerators are currently the most widely used machines in radiation therapy centers. methods: in this work, a monte carlo modelling of the siemens oncor linear accelerator in 6 mv and 18 mv beams was performed. the results of simulation were validated by measurements in wat...